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  • 1.
    Abrate, Matteo
    et al.
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Bacciu, Clara
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Marchetti, Andrea
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Minutoli, Salvatore
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Tesconi, Maurizio
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Geomemories - A Platform for Visualizing Historical, Environmental and Geospatial Changes of the Italian Landscape2013In: ISPRS International Journal of Geo-Information. Special issue: Geospatial Monitoring and Modelling of Environmental Change, ISSN 2220-9964, Vol. 2, no 2, p. 432-455Article in journal (Refereed)
    Abstract [en]

    The GeoMemories project aims at publishing on the Web and digitally preserving historical aerial photographs that are currently stored in physical form within the archives of the Aerofototeca Nazionale in Rome. We describe a system, available at http://www.geomemories.org, that lets users visualize the evolution of the Italian landscape throughout the last century. The Web portal allows comparison of recent satellite imagery with several layers of historical maps, obtained from the aerial photos through a complex workflow that merges them together. We present several case studies carried out in collaboration with geologists, historians and archaeologists, that illustrate the great potential of our system in different research fields. Experiments and advances in image processing technologies are envisaged as a key factor in solving the inherent issue of vast amounts of manual work, from georeferencing to mosaicking to analysis.

  • 2.
    Azar, Jimmy C.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Simonsson, Martin
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Image segmentation and identification of paired antibodies in breast tissue2014In: Computational & Mathematical Methods in Medicine, ISSN 1748-670X, E-ISSN 1748-6718, p. 647273:1-11Article in journal (Refereed)
    Abstract [en]

    Comparing staining patterns of paired antibodies designed towards a specific protein but toward different epitopes of the protein provides quality control over the binding and the antibodies' ability to identify the target protein correctly and exclusively. We present a method for automated quantification of immunostaining patterns for antibodies in breast tissue using the Human Protein Atlas database. In such tissue, dark brown dye 3,3'-diaminobenzidine is used as an antibody-specific stain whereas the blue dye hematoxylin is used as a counterstain. The proposed method is based on clustering and relative scaling of features following principal component analysis. Our method is able (1) to accurately segment and identify staining patterns and quantify the amount of staining and (2) to detect paired antibodies by correlating the segmentation results among different cases. Moreover, the method is simple, operating in a low-dimensional feature space, and computationally efficient which makes it suitable for high-throughput processing of tissue microarrays.

  • 3.
    Azar, Jimmy
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Simonsson, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Automated Classification of Glandular Tissue by Statistical Proximity Sampling2015In: International Journal of Biomedical Imaging, ISSN 1687-4188, E-ISSN 1687-4196, article id 943104Article in journal (Refereed)
    Abstract [en]

    Due to the complexity of biological tissue and variations in staining procedures, features that are based on the explicit extraction of properties from subglandular structures in tissue images may have difficulty generalizing well over an unrestricted set of images and staining variations. We circumvent this problem by an implicit representation that is both robust and highly descriptive, especially when combined with a multiple instance learning approach to image classification. The new feature method is able to describe tissue architecture based on glandular structure. It is based on statistically representing the relative distribution of tissue components around lumen regions, while preserving spatial and quantitative information, as a basis for diagnosing and analyzing different areas within an image. We demonstrate the efficacy of the method in extracting discriminative features for obtaining high classification rates for tubular formation in both healthy and cancerous tissue, which is an important component in Gleason and tubule-based Elston grading. The proposed method may be used for glandular classification, also in other tissue types, in addition to general applicability as a region-based feature descriptor in image analysis where the image represents a bag with a certain label (or grade) and the region-based feature vectors represent instances.

  • 4.
    Barrera, Tony
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    A chronological and mathematical overview of digital circle generation algorithms: Introducing efficient 4- and 8-connected circles2016In: International Journal of Computer Mathematics, ISSN 0020-7160, E-ISSN 1029-0265, Vol. 93, no 8, p. 1241-1253Article in journal (Refereed)
    Abstract [en]

    Circles are one of the basic drawing primitives for computers and while the naive way of setting up an equation for drawing circles is simple, implementing it in an efficient way using integer arithmetic has resulted in quite a few different algorithms. We present a short chronological overview of the most important publications of such digital circle generation algorithms. Bresenham is often assumed to have invented the first all integer circle algorithm. However, there were other algorithms published before his first official publication, which did not use floating point operations. Furthermore, we present both a 4- and an 8-connected all integer algorithm. Both of them proceed without any multiplication, using just one addition per iteration to compute the decision variable, which makes them more efficient than previously published algorithms.

  • 5. Barrera, Tony
    et al.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    An Algorithm for Parallel Calculation of Trigonometric and Exponential Functions2013In: ACM International Conference on Computing Frontiers, 2013Conference paper (Refereed)
  • 6. Estevez, B.
    et al.
    Pazos, M.
    Franco, J. M.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Recreating with photogrammetric techniques a submerged megalithic landscape: the case of the salas reservoir2015In: 3 Encontro Internacional de Arqueoloxia de Vilalba, 2015, p. 9-16Conference paper (Refereed)
  • 7.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    3D Stereoscopic Rendering: An Overview of Implementation Issues2010In: Game Engine Gems / [ed] Eric Lengyel, 2010, p. 123-138Chapter in book (Other (popular science, discussion, etc.))
  • 8.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    How to Promote Student Creativity and Learning using Tutorials in Teaching Graphics and Visualisation2014In: Proc. 16th International Conference on Geometry and Graphics, Innsbruck University Press, 2014, p. 626-633Conference paper (Other academic)
  • 9.
    Hast, Anders
    Uppsala University, Interfaculty Units, Centre for Image Analysis.
    Improved Fundamental Algorithms for Fast Computer Graphics2002Licentiate thesis, monograph (Other scientific)
  • 10.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Interest Point Detection Based on the Extended Structure Tensor with a Scale Space Parameter2015In: International Conference on Computer Vision Theory and Applications, 2015, p. 1-8Conference paper (Refereed)
  • 11.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Mathematics + Computer Science = True2015Conference paper (Refereed)
  • 12.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Robust and Invariant Phase Based Local Feature Matching2014In: 22nd International Conference on Pattern Recognition (ICPR), 2014, 2014, p. 809-814Conference paper (Refereed)
    Abstract [en]

    Any feature matching algorithm needs to be robust, producing few false positives but also needs to be invariant to changes in rotation, illumination and scale. Several improvements are proposed to a previously published Phase Correlation based algorithm, which operates on local disc areas, using the Log Polar Transform to sample the disc neighborhood and the FFT to obtain the phase. It will be shown that the matching can be done in the frequency domain directly, using the Chi-squared distance, instead of computing the cross power spectrum. Moreover, it will be shown how combining these methods yields an algorithm that sorts out a majority of the false positives. The need for a peak to sub lobe ratio computation in order to cope with sub pixel accuracy will be discussed as well as how the FFT of the periodic component can enhance the matching. The result is a robust local feature matcher that is able to cope with rotational, illumination and scale differences to a certain degree.

  • 13.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Simple filter design for first and second order derivatives by a double filtering approach2014In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 42, p. 65-71Article in journal (Refereed)
    Abstract [en]

    Spline filters are usually implemented in two steps, where in the first step the basis coefficients are computed by deconvolving the sampled function with a factorized filter and the second step reconstructs the sampled function. It will be shown how separable spline filters using different splines can be constructed with fixed kernels, requiring no inverse filtering. Especially, it is discussed how first and second order derivatives can be computed correctly using cubic or trigonometric splines by a double filtering approach giving filters of length 7.

  • 14.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Barrera, Tony
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    A modified Phong-Blinn light model for shadowed areas2003In: Graphics programming methods / [ed] Jeff Lander, Hingham: Charles River Media , 2003, p. 231-235Chapter in book (Refereed)
  • 15.
    Hast, Anders
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Barrera, Tony
    Bengtsson, Ewert
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    A modified Phong-Blinn light model for shadowed areas2003In: Proceedings of 3rd conference for the promotion of research in IT, 2003Conference paper (Other scientific)
  • 16.
    Hast, Anders
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Barrera, Tony
    Bengtsson, Ewert
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Incremental Spherical Interpolation with Quadratically Varying Angle2006In: SIGRAD 2006. The Annual SIGRAD Conference, Special Theme: Computer Games, November 22–23, 2006, Skövde, Sweden, 2006Conference paper (Refereed)
    Abstract [en]

    Spherical linear interpolation has got a number of important applications in computer graphics. We show how spherical interpolation can be performed efficiently even for the case when the angle vary quadratically over the interval. The computation will be fast since the implementation does not need to evaluate any trigonometric functions in the inner loop. Furthermore, no renormalization is necessary and therefore it is a true spherical interpolation. This type of interpolation, with non equal angle steps, should be useful for animation with accelerating or decelerating movements, or perhaps even in other types of applications.

  • 17.
    Hast, Anders
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Barrera, Tony
    Bengtsson, Ewert
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Reconstruction Filters for Bump Mapping2002In: Proceedings from Promote IT 2002, 2002, p. 244-256Conference paper (Other scientific)
  • 18.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Capurro, Carlotta
    Nollet, Dries
    Pletinckx, Daniel
    Estevez, B.
    Pazos, M.
    Franco, J. M.
    Marchetti, Andrea
    Stereo Visualisation of Historical Aerial Photos: A Useful and Important Aerial Archeology Research Tool2016Conference paper (Refereed)
  • 19.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Cullhed, Per
    Uppsala University, University Library.
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    TexT – Text extractor tool for handwritten document transcription and annotation2018In: Digital Libraries and Multimedia Archives, Springer, 2018, p. 81-92Conference paper (Refereed)
    Abstract [en]

    This paper presents a framework for semi-automatic transcription of large-scale historical handwritten documents and proposes a simple user-friendly text extractor tool, TexT for transcription. The proposed approach provides a quick and easy transcription of text using computer assisted interactive technique. The algorithm finds multiple occurrences of the marked text on-the-fly using a word spotting system. TexT is also capable of performing on-the-fly annotation of handwritten text with automatic generation of ground truth labels, and dynamic adjustment and correction of user generated bounding box annotations with the word being perfectly encapsulated. The user can view the document and the found words in the original form or with background noise removed for easier visualization of transcription results. The effectiveness of TexT is demonstrated on an archival manuscript collection from well-known publicly available dataset.

  • 20.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Fornés, Alicia
    Univ Autonoma Barcelona, Comp Vis Ctr, Dept Comp Sci, Bellaterra, Spain.
    A segmentation-free handwritten word spotting approach by relaxed feature matching2016In: Proc. 12th IAPR Workshop on Document Analysis Systems, IEEE, 2016, p. 150-155Conference paper (Refereed)
    Abstract [en]

    The automatic recognition of historical handwritten documents is still considered a challenging task. For this reason, word spotting emerges as a good alternative for making the information contained in these documents available to the user. Word spotting is defined as the task of retrieving all instances of the query word in a document collection, becoming a useful tool for information retrieval. In this paper we propose a segmentation-free word spotting approach able to deal with large document collections. Our method is inspired on feature matching algorithms that have been applied to image matching and retrieval. Since handwritten words have different shape, there is no exact transformation to be obtained. However, the sufficient degree of relaxation is achieved by using a Fourier based descriptor and an alternative approach to RANSAC called PUMA. The proposed approach is evaluated on historical marriage records, achieving promising results.

  • 21.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Hanke, Michael
    Royal Inst Technol, KTH, Dept Math, Sch Engn Sci, Stockholm, Sweden.
    Karlsson, Hans O.
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - Ångström, Theoretical Chemistry.
    Swedish eScience Education – a Graduate School in eScience2015In: Proc. 11th International Conference on e-Science, IEEE Computer Society, 2015, p. 31-35Conference paper (Refereed)
    Abstract [en]

    Swedish eScience Education (SeSE) is a national graduate school in eScience in Sweden. It comes from the collaboration between two major research initiatives in eScience and the school has turned out to be very successful. It has made it possible for students at different universities to get access to education that is not normally available at their home universities. With SeSE they get access to education by the top experts within their respective field. We argue why such graduate school is important and how it is different from training offered by many HPC centres in Europe. Furthermore, examples of courses and their structure is discussed as well as lessons learned from SeSE and its two predecessors in Sweden.

  • 22.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Jenke, Peter
    University of Gävle.
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Shortest Diagonal Triangulation of Convex Layers2013In: The IASTED International Conference on Signal Processing, Pattern Recognition and Applications., 2013, p. 1-7Conference paper (Refereed)
  • 23.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Kylberg, Gustav
    Clustering in 2D as a Fast Deterministic Alternative to RANSAC2015Conference paper (Refereed)
  • 24.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Kylberg, Gustav
    Sintorn, Ida-Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    An efficient descriptor based on radial line integration for fast non invariant matching and registration of microscopy images2017In: Advanced Concepts for Intelligent Vision Systems, Springer, 2017, p. 723-734Conference paper (Refereed)
  • 25.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Marchetti, Andrea
    Institute of Informatics and Telematics, Pisa, Italy.
    Putative Match Analysis: A Repeatable Alternative to RANSAC for Matching of Aerial Images2012In: VISAPP 2012 - Proceedings of the International Conference on Computer Vision Theory and Applications, Volume 2 / [ed] Gabriela Csurka, José Braz, SciTePress , 2012, p. 341-344Conference paper (Refereed)
    Abstract [en]

     One disadvantage with RANSAC is that it is based on randomness and will therefore often yield a different set of inliers in each run, especially if the dataset contains a large number of outliers. A repeatable algorithm for finding both matches and the homography is proposed, which in our case is used for image stitching and the obtained points are also used for georeferencing. This algorithm will yield the same set of matches every time and is therefore a useful tool when trying to evaluate other algorithms involved and their parameters. Moreover a refining step is proposed that finds the best matches depending on what geometric transformation is used, which also can be utilized as a refining step for RANSAC. 

  • 26.
    Hast, Anders
    et al.
    Institute of Informatics and Telematics, CNR, Pisa, Italy.
    Marchetti, Andrea
    Institute of Informatics and Telematics, Pisa, Italy.
    Putative Match Analysis: A Repeatable Alternative to RANSAC for Matching of Aerial Images2012In: VISAPP 2012 - Proceedings of the International Conference on Computer Vision Theory and Applications, Volume 2 / [ed] Gabriela Csurka, José Braz, SciTePress , 2012, p. 341-344Conference paper (Refereed)
    Abstract [en]

     One disadvantage with RANSAC is that it is based on randomness and will therefore often yield a different set of inliers in each run, especially if the dataset contains a large number of outliers. A repeatable algorithm for finding both matches and the homography is proposed, which in our case is used for image stitching and the obtained points are also used for georeferencing. This algorithm will yield the same set of matches every time and is therefore a useful tool when trying to evaluate other algorithms involved and their parameters. Moreover a refining step is proposed that finds the best matches depending on what geometric transformation is used, which also can be utilized as a refining step for RANSAC. 

  • 27.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Marchetti, Andrea
    IIT, CNR.
    Rotation Invariant Feature Matching - Based on Gaussian Filtered Log Polar Transform and Phase Correlation.2013In: 8th International Symposium on Image and Signal Processing and Analysis: (ISPA 2013), 2013, p. 1-6Conference paper (Refereed)
    Abstract [en]

    Rotation invariance is an important property for any feature matching method and it has been implemented in different ways for different methods. The Log Polar Transform has primarily been used for image registration where it is applied after phase correlation, which in its turn is applied on the whole images or in the case of template matching, applied on major parts of them followed by an exhaustive search. We investigate how this transform can be used on local neighborhoods of features and how phase correlation as well as normalized cross correlation can be applied on the result. Thus, the order is reversed and we argue why it is important to do so. We demonstrate a common problem with the log polar transform and that many implementations of it are not suitable for local feature detectors. We propose an implementation of it based on Gaussian filtering. We also show that phase correlation generally will perform better than normalized cross correlation. Both handles illumination differences well, but changes in scale is handled better by the phase correlation approach. 

  • 28.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Marchetti, Andrea
    CNR, Ist Informat & Telemat, Pisa, Italy.
    Stereo Visualisation of Historical Aerial Photos – a Valuable Digital Heritage Research Tool2015In: 2015 Digital Heritage International Congress, Vol 2: Analysis & Interpretation Theory, Methodologies, Preservation & Standards Digital Heritage Projects & Applications, 2015, p. 663-666Conference paper (Refereed)
    Abstract [en]

    We demonstrate with several examples how historical aerial photos can benefit from being viewed in stereo and how this can be useful as tool in digital heritage research. The main reason why stereo images are important is that they give a much better understanding of what is actually in the scene than single photos can. The important factor is the depth cue that helps understanding the content and adds the ability to distinguish between objects such as houses and trees and the ground as well as estimating heights of objects. There are however still challenges but also possibilities that will be discussed.

  • 29.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Marchetti, Andrea
    Stereo Visualisation of Historical Aerial Photos as a Valuable Tool for Archeological Research2015In: Computer Applications and Quantitative Methods in Archaeology, CAA, 2015, p. 1-3Conference paper (Refereed)
  • 30.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Marchetti, Andrea
    The Challenges and Advantages with a Parallel Implementation of Feature Matching2016In: Proc. 11th International Conference on Computer Vision Theory and Applications, 2016Conference paper (Refereed)
  • 31.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Nysjö, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Optimal RANSAC - Towards a Repeatable Algorithm for Finding the Optimal Set2013In: Journal of WSCG, ISSN 1213-6972, E-ISSN 1213-6964, Vol. 21, no 1, p. 21-30Article in journal (Refereed)
  • 32.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Sablina, Victoria A.
    Sintorn, Ida-Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Kylberg, Gustaf
    A fast Fourier based feature descriptor and a cascade nearest neighbour search with an efficient matching pipeline for mosaicing of microscopy images2018In: Pattern Recognition and Image Analysis, ISSN 1054-6618, Vol. 28, no 2, p. 261-272Article in journal (Refereed)
  • 33.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Sablina, Victoria
    Kylberg, Gustav
    Sintorn, Ida-Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    A Simple and Efficient Feature Descriptor for Fast Matching2015In: WSCG / [ed] V. Skala, 2015, p. 135-142Conference paper (Refereed)
  • 34.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    An intelligent user interface for efficient semi-automatic transcription of historical handwritten documents2018In: Proc. 23rd International Conference on Intelligent User Interfaces Companion, New York: ACM Press, 2018, article id 48Conference paper (Refereed)
  • 35.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Radial line Fourier descriptor for historical handwritten text representation2018In: Journal of WSCG, ISSN 1213-6972, E-ISSN 1213-6964, Vol. 26, no 1, p. 31-40Article in journal (Refereed)
  • 36.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Radial line Fourier descriptor for historical handwritten text representation2018In: Proc. 26th International Conference on Computer Graphics: Visualization and Computer Vision, 2018Conference paper (Other academic)
    Abstract [en]

    Automatic recognition of historical handwritten manuscripts is a daunting task due to paper degradation over time. Recognition-free retrieval or word spotting is popularly used for information retrieval and digitization of the historical handwritten documents. However, the performance of word spotting algorithms depends heavily on feature detection and representation methods. Although there exist popular feature descriptors such as Scale Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF), the invariant properties of these descriptors amplify the noise in the degraded document images, rendering them more sensitive to noise and complex characteristics of historical manuscripts. Therefore, an efficient and relaxed feature descriptor is required as handwritten words across different documents are indeed similar, but not identical. This paper introduces a Radial Line Fourier (RLF) descriptor for handwritten word representation, with a short feature vector of 32 dimensions. A segmentation-free and training-free handwritten word spotting method is studied herein that relies on the proposed RLF descriptor, takes into account different keypoint representations and uses a simple preconditioner-based feature matching algorithm. The effectiveness of the RLF descriptor for segmentation-free handwritten word spotting is empirically evaluated on well-known historical handwritten datasets using standard evaluation measures.

  • 37.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Weidendorfer, Josef
    Weiss, Jan-Philipp
    UCHPC 2012: Fifth Workshop on UnConventional High Performance Computing2013In: Euro-Par 2012: Parallel Processing Workshops, Springer Berlin/Heidelberg, 2013, Vol. 7640, p. 505-506Conference paper (Refereed)
  • 38. Malapelle, Francesco
    et al.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Fusiello, Andrea
    Rossi, B.
    Fragneto, P.
    Marchetti, Andrea
    Automatic 3DS Conversion of Historical Aerial Photographs2015In: IC3D 2015, International Conference on 3D Imaging, 2015Conference paper (Refereed)
    Abstract [en]

    In this paper we present a method for the generation of 3D stereo (3DS) pairs from sequences of historical aerial photographs. The goal of our work is to provide a stereoscopic display when the existing exposures are in a monocular sequence. Each input image is processed using its neighbours and a synthetic image is rendered, which, together with the original one, form a stereo pair. Promising results on real images taken from a historical photo archive are shown, that corroborate the viability of generating 3DS data from monocular footage.

  • 39.
    Matuszewski, Damian J.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab. Science for Life Laboratory, Uppsala, Sweden.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Sintorn, Ida-Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    A short feature vector for image matching: The Log-Polar Magnitude feature descriptor2017In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 11, article id e0188496Article in journal (Refereed)
    Abstract [en]

    The choice of an optimal feature detector-descriptor combination for image matching often depends on the application and the image type. In this paper, we propose the Log-Polar Magnitude feature descriptor—a rotation, scale, and illumination invariant descriptor that achieves comparable performance to SIFT on a large variety of image registration problems but with much shorter feature vectors. The descriptor is based on the Log-Polar Transform followed by a Fourier Transform and selection of the magnitude spectrum components. Selecting different frequency components allows optimizing for image patterns specific for a particular application. In addition, by relying only on coordinates of the found features and (optionally) feature sizes our descriptor is completely detector independent. We propose 48- or 56-long feature vectors that potentially can be shortened even further depending on the application. Shorter feature vectors result in better memory usage and faster matching. This combined with the fact that the descriptor does not require a time-consuming feature orientation estimation (the rotation invariance is achieved solely by using the magnitude spectrum of the Log-Polar Transform) makes it particularly attractive to applications with limited hardware capacity. Evaluation is performed on the standard Oxford dataset and two different microscopy datasets; one with fluorescence and one with transmission electron microscopy images. Our method performs better than SURF and comparable to SIFT on the Oxford dataset, and better than SIFT on both microscopy datasets indicating that it is particularly useful in applications with microscopy images.

  • 40.
    Nysjö, Johan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Teaching OpenGL and Computer Graphics with Programmable Shaders2015In: SIGRAD, 2015, p. 1-3Conference paper (Refereed)
  • 41. Pihlström, Max
    et al.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Triangulation Painting2015In: SIGRAD, 2015, p. 1-4Conference paper (Refereed)
  • 42.
    Singh, Prashant
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
    Vats, Ekta
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Learning surrogate models of document image quality metrics for automated document image processing2018In: Proc. 13th IAPR Workshop on Document Analysis Systems, IEEE, 2018, p. 67-72Conference paper (Refereed)
  • 43.
    Vats, Ekta
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    On-the-fly historical handwritten text annotation2017In: Proc. 14th IAPR International Conference on Document Analysis and Recognition: Volume 8, IEEE, 2017, p. 10-14Conference paper (Refereed)
  • 44.
    Vats, Ekta
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Mårtensson, Lasse
    Extracting script features from a large corpus of handwritten documents2018In: Digital Humanities in the Nordic Countries: Book of Abstracts, 2018Conference paper (Refereed)
  • 45.
    Vats, Ekta
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Singh, Prashant
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
    Automatic document image binarization using Bayesian optimization2017In: Proc. 4th International Workshop on Historical Document Imaging and Processing, New York: ACM Press, 2017, p. 89-94Conference paper (Refereed)
1 - 45 of 45
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