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  • 951.
    Åhlén, Julia
    et al.
    Högskolan i Gävle.
    Seipel, Stefan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    TIME-SPACE VISUALISATION OF AMUR RIVER CHANNEL CHANGES DUE TO FLOODING DISASTER2014Inngår i: Proceedings of International Multidisciplinary Scientific GeoScience Conference (SGEM), 2014, 2014Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The analysis of flooding levels is a highly complex temporal and spatial assessment task that involves estimation of distances between references in geographical space as well as estimations of instances along the time-line that coincide with given spatial locations. This work has an aim to interactively explore changes of Amur River boundaries caused by the severe flooding in September 2013. In our analysis of river bank changes we use satellite imagery (Landsat 7) to extract parts belonging to Amur River. We use imagery from that covers time interval July 2003 until February 2014. Image data is pre-processed using low level image processing techniques prior to visualization. Pre-processing has a purpose to extract information about the boundaries of the river, and to transform it into a vectorized format, suitable as inputs subsequent visualization. We develop visualization tools to explore the spatial and temporal relationship in the change of river banks. In particular the visualization shall allow for exploring specific geographic locations and their proximity to the river/floods at arbitrary times. We propose a time space visualization that emanates from edge detection, morphological operations and boundary statistics on Landsat 2D imagery in order to extract the borders of Amur River. For the visualization we use the time-spacecube metaphor. It is based on a 3D rectilinear context, where the 2D geographical coordinate system is extended with a time-axis pointing along the 3rd Cartesian axis. Such visualization facilitates analysis of the channel shape of Amur River and thus enabling for a conclusion regarding the defined problem. As a result we demonstrate our time-space visualization for river Amur and using some amount of geographical point data as a reference we suggest an adequate method of interpolation or imputation that can be employed to estimate value at a given location and time.

  • 952.
    Åhlén, Julia
    et al.
    Högskolan i Gävle.
    Seipel, Stefan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Liu, Fei
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Evaluation of the Automatic methods for Building Extraction2014Inngår i: International Journal of Computers and Communications, ISSN 2074-1294, Vol. 8, s. 171-176Artikkel i tidsskrift (Fagfellevurdert)
  • 953.
    Öfverstedt, Johan
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Lindblad, Joakim
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Serbian Acad Arts & Sci, Math Inst, Belgrade 11001, Serbia.
    Sladoje, Natasa
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Serbian Acad Arts & Sci, Math Inst, Belgrade 11001, Serbia.
    Fast and Robust Symmetric Image Registration Based on Distances Combining Intensity and Spatial Information2019Inngår i: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 28, nr 7, s. 3584-3597Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Intensity-based image registration approaches rely on similarity measures to guide the search for geometric correspondences with high affinity between images. The properties of the used measure are vital for the robustness and accuracy of the registration. In this study a symmetric, intensity interpolation-free, affine registration framework based on a combination of intensity and spatial information is proposed. The excellent performance of the framework is demonstrated on a combination of synthetic tests, recovering known transformations in the presence of noise, and real applications in biomedical and medical image registration, for both 2D and 3D images. The method exhibits greater robustness and higher accuracy than similarity measures in common use, when inserted into a standard gradientbased registration framework available as part of the open source Insight Segmentation and Registration Toolkit (ITK). The method is also empirically shown to have a low computational cost, making it practical for real applications. Source code is available.

    Fulltekst (pdf)
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  • 954.
    Öfverstedt, Johan
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Lindblad, Joakim
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Sladoje, Natasa
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Fast and Robust Symmetric Image Registration Based on Intensity and Spatial Information2018Manuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

    Intensity-based image registration approaches rely on similarity measures to guide the search for geometric correspondences with high affinity between images. The properties of the used measure are vital for the robustness and accuracy of the registration. In this study a symmetric, intensity interpolation-free, affine registration framework based on a combination of intensity and spatial information is proposed. The excellent performance of the framework is demonstrated on a combination of synthetic tests, recovering known transformations in the presence of noise, and real applications in biomedical and medical image registration, for both 2D and 3D images. The method exhibits greater robustness and higher accuracy than similarity measures in common use, when inserted into a standard gradient-based registration framework available as part of the open source Insight Segmentation and Registration Toolkit (ITK). The method is also empirically shown to have a low computational cost, making it practical for real applications. Source code is available.

  • 955.
    Öfverstedt, Johan
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Lindblad, Joakim
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Sladoje, Natasa
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Robust Symmetric Affine Image Registration2019Inngår i: Swedish Symposium on Image Analysis, 2019Konferansepaper (Annet vitenskapelig)
  • 956.
    Öfverstedt, Johan
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Lindblad, Joakim
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Sladoje, Natasa
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Stochastic Distance Functions with Applications in Object Detection and Image Segmentation2019Inngår i: Swedish Symposium on Image Analysis, 2019Konferansepaper (Annet vitenskapelig)
  • 957.
    Öfverstedt, Johan
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Lindblad, Joakim
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Sladoje, Natasa
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Stochastic Distance Transform2019Inngår i: Discrete Geometry for Computer Imagery, Springer, 2019, s. 75-86Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The distance transform (DT) and its many variations are ubiquitous tools for image processing and analysis. In many imaging scenarios, the images of interest are corrupted by noise. This has a strong negative impact on the accuracy of the DT, which is highly sensitive to spurious noise points. In this study, we consider images represented as discrete random sets and observe statistics of DT computed on such representations. We, thus, define a stochastic distance transform (SDT), which has an adjustable robustness to noise. Both a stochastic Monte Carlo method and a deterministic method for computing the SDT are proposed and compared. Through a series of empirical tests, we demonstrate that the SDT is effective not only in improving the accuracy of the computed distances in the presence of noise, but also in improving the performance of template matching and watershed segmentation of partially overlapping objects, which are examples of typical applications where DTs are utilized.

  • 958.
    Öfverstedt, Johan
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Sladoje, Natasa
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Lindblad, Joakim
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Distance between vector-valued fuzzy sets based on intersection decomposition with applications in object detection2017Inngår i: Mathematical Morphology and its Applications to Signal and Image Processing, Springer, 2017, Vol. 10225, s. 395-407Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We present a novel approach to measuring distance between multi-channel images, suitably represented by vector-valued fuzzy sets. We first apply the intersection decomposition transformation, based on fuzzy set operations, to vector-valued fuzzy representations to enable preservation of joint multi-channel properties represented in each pixel of the original image. Distance between two vector-valued fuzzy sets is then expressed as a (weighted) sum of distances between scalar-valued fuzzy components of the transformation. Applications to object detection and classification on multi-channel images and heterogeneous object representations are discussed and evaluated subject to several important performance metrics. It is confirmed that the proposed approach outperforms several alternative single-and multi-channel distance measures between information-rich image/ object representations.

  • 959.
    Öfverstedt, Johan
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Sladoje, Natasa
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Lindblad, Joakim
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Distance Between Vector-valued Images based on Intersection Decomposition with Applications in Object Detection2018Inngår i: Swedish Symposium on Image Analysis, 2018Konferansepaper (Annet vitenskapelig)
  • 960.
    Ćurić, Vladimir
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Distance Functions and Their Use in Adaptive Mathematical Morphology2014Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    One of the main problems in image analysis is a comparison of different shapes in images. It is often desirable to determine the extent to which one shape differs from another. This is usually a difficult task because shapes vary in size, length, contrast, texture, orientation, etc. Shapes can be described using sets of points, crisp of fuzzy. Hence, distance functions between sets have been used for comparing different shapes.

    Mathematical morphology is a non-linear theory related to the shape or morphology of features in the image, and morphological operators are defined by the interaction between an image and a small set called a structuring element. Although morphological operators have been extensively used to differentiate shapes by their size, it is not an easy task to differentiate shapes with respect to other features such as contrast or orientation. One approach for differentiation on these type of features is to use data-dependent structuring elements.

    In this thesis, we investigate the usefulness of various distance functions for: (i) shape registration and recognition; and (ii) construction of adaptive structuring elements and functions.

    We examine existing distance functions between sets, and propose a new one, called the Complement weighted sum of minimal distances, where the contribution of each point to the distance function is determined by the position of the point within the set. The usefulness of the new distance function is shown for different image registration and shape recognition problems. Furthermore, we extend the new distance function to fuzzy sets and show its applicability to classification of fuzzy objects.

    We propose two different types of adaptive structuring elements from the salience map of the edge strength: (i) the shape of a structuring element is predefined, and its size is determined from the salience map; (ii) the shape and size of a structuring element are dependent on the salience map. Using this salience map, we also define adaptive structuring functions. We also present the applicability of adaptive mathematical morphology to image regularization. The connection between adaptive mathematical morphology and Lasry-Lions regularization of non-smooth functions provides an elegant tool for image regularization.

    Delarbeid
    1. On set distances and their application to image registration
    Åpne denne publikasjonen i ny fane eller vindu >>On set distances and their application to image registration
    2009 (engelsk)Inngår i: Proc. 6th International Symposium on Image and Signal Processing and Analysis, Salzburg, Austria: IEEE , 2009, s. 449-454Konferansepaper, Publicerat paper (Fagfellevurdert)
    Abstract [en]

    In this paper we study set distances that are used in image processing. We propose a generalization of Sum of minimal distances and show that its special cases include a metric by Symmetric difference. The Hausdorff metric and the Chamfer matching distances are also closely related with the presented framework. In addition, we define the Complement set distance of a given distance. We evaluate the observed distance with respect to applicability to image object registration. We perform comparative evaluations with respect to noise sensitivity, as well as with respect to rigid body transformations. We conclude that the family of Generalized sum of minimal distances has many desirable properties for this application.

    sted, utgiver, år, opplag, sider
    Salzburg, Austria: IEEE, 2009
    HSV kategori
    Forskningsprogram
    Datoriserad bildanalys; Datoriserad bildbehandling
    Identifikatorer
    urn:nbn:se:uu:diva-110684 (URN)10.1109/ISPA.2009.5297672 (DOI)978-953-184-135-1 (ISBN)
    Konferanse
    6th International Symposium on Image and Signal Processing and Analysis, Salzburg, Austria, 16-18 September, 2009
    Tilgjengelig fra: 2009-11-26 Laget: 2009-11-23 Sist oppdatert: 2018-12-18
    2. A new set distance and its application to shape registration
    Åpne denne publikasjonen i ny fane eller vindu >>A new set distance and its application to shape registration
    Vise andre…
    2014 (engelsk)Inngår i: Pattern Analysis and Applications, ISSN 1433-7541, E-ISSN 1433-755X, Vol. 17, nr 1, s. 141-152Artikkel i tidsskrift (Fagfellevurdert) Published
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-220413 (URN)10.1007/s10044-012-0290-x (DOI)000330839400011 ()
    Tilgjengelig fra: 2012-08-23 Laget: 2014-03-13 Sist oppdatert: 2018-12-18bibliografisk kontrollert
    3. Distance measures between digital fuzzy objects and their applicability in image processing
    Åpne denne publikasjonen i ny fane eller vindu >>Distance measures between digital fuzzy objects and their applicability in image processing
    2011 (engelsk)Inngår i: Combinatorial Image Analysis / [ed] Jake Aggarwal, Reneta Barneva, Valentin Brimkov, Kostadin Koroutchev, Elka Koroutcheva, Springer Berlin/Heidelberg, 2011, s. 385-397Konferansepaper, Publicerat paper (Fagfellevurdert)
    Abstract [en]

    We present two different extensions of the Sum of minimal distances and the Complement weighted sum of minimal distances to distances between fuzzy sets. We evaluate to what extent the proposed distances show monotonic behavior with respect to increasing translation and rotation of digital objects, in noise free, as well as in noisy conditions. Tests show that one of the extension approaches leads to distances exhibiting very good performance. Furthermore, we evaluate distance based classification of crisp and fuzzy representations of objects at a range of resolutions. We conclude that the proposed distances are able to utilize the additional information available in a fuzzy representation, thereby leading to improved performance of related image processing tasks.

    sted, utgiver, år, opplag, sider
    Springer Berlin/Heidelberg, 2011
    Serie
    Lecture Notes in Computer Science ; 6636
    Emneord
    Fuzzy sets, set distance, registration, classification
    HSV kategori
    Forskningsprogram
    Datoriserad bildanalys; Datoriserad bildbehandling
    Identifikatorer
    urn:nbn:se:uu:diva-157186 (URN)10.1007/978-3-642-21073-0_34 (DOI)978-3-642-21072-3 (ISBN)
    Konferanse
    Internatiional Workshop on Combinatorial Image Analysis, IWCIA 2011
    Tilgjengelig fra: 2011-08-18 Laget: 2011-08-18 Sist oppdatert: 2018-12-18
    4. Salience adaptive structuring elements
    Åpne denne publikasjonen i ny fane eller vindu >>Salience adaptive structuring elements
    2012 (engelsk)Inngår i: IEEE Journal on Selected Topics in Signal Processing, ISSN 1932-4553, E-ISSN 1941-0484, Vol. 6, nr 7, s. 809-819Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    Spatially adaptive structuring elements adjust their shape to the local structures in the image, and are often defined by a ball in a geodesic distance or gray-weighted distance metric space. This paper introduces salience adaptive structuring elements as spatially variant structuring elements that modify not only their shape, but also their size according to the salience of the edges in the image. Morphological operators with salience adaptive structuring elements shift edges with high salience to a less extent than those with low salience. Salience adaptive structuring elements are less flexible than morphological amoebas and their shape is less affected by noise in the image. Consequently, morphological operators using salience adaptive structuring elements have better properties.

    Emneord
    Adaptive mathematical morphology, anisotropic filtering, morphological amoebas, salience distance transform
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-181248 (URN)10.1109/JSTSP.2012.2207371 (DOI)000310138400007 ()
    Tilgjengelig fra: 2012-09-20 Laget: 2012-09-20 Sist oppdatert: 2017-12-07bibliografisk kontrollert
    5. Adaptive structuring elements based on salience information
    Åpne denne publikasjonen i ny fane eller vindu >>Adaptive structuring elements based on salience information
    2012 (engelsk)Inngår i: Computer Vision and Graphics / [ed] L. Bolc, K. Wojciechowski, R. Tadeusiewicz, L.J. Chmielewski, Springer, 2012, s. 321-328Konferansepaper, Publicerat paper (Annet vitenskapelig)
    Abstract [en]

    Adaptive structuring elements modify their shape and size according to the image content and may outperform fixed structuring elements. Without any restrictions, they suffer from a high computational complexity, which is often higher than linear with respect to the number of pixels in the image. This paper introduces adaptive structuring elements that have predefined shape, but where the size is adjusted to the local image structures. The size of adaptive structuring elements is determined by the salience map that corresponds to the salience of the edges in the image, which can be computed in linear time. We illustrate the difference between the new adaptive structuring elements and morphological amoebas. As an example of its usefulness, we show how the new adaptive morphological operations can isolate the text in historical documents.

    sted, utgiver, år, opplag, sider
    Springer, 2012
    Serie
    Lecture Notes in Computer Science, ISSN 03029743 ; 7594
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-181246 (URN)10.1007/978-3-642-33564-8-39 (DOI)000313005700039 ()978-3-642-33564-8 (ISBN)
    Konferanse
    International Conference on Computer Vision and Graphics, September 24-26, 2012, Warsaw, Poland
    Tilgjengelig fra: 2012-09-20 Laget: 2012-09-20 Sist oppdatert: 2018-01-12bibliografisk kontrollert
    6. Salience-Based Parabolic Structuring Functions
    Åpne denne publikasjonen i ny fane eller vindu >>Salience-Based Parabolic Structuring Functions
    2013 (engelsk)Inngår i: Mathematical Morphology and Its Applications to Signal and Image Processing, Springer Berlin/Heidelberg, 2013, s. 183-194Konferansepaper, Publicerat paper (Fagfellevurdert)
    Abstract [en]

    It has been shown that the use of the salience map based on the salience distance transform can be useful for the construction of spatially adaptive structuring elements. In this paper, we propose salience-based parabolic structuring functions that are defined for a fixed, predefined spatial support, and have low computational complexity. In addition, we discuss how to properly define adjunct morphological operators using the new spatially adaptive structuring functions. It is also possible to obtain flat adaptive structuring elements by thresholding the salience-based parabolic structuring functions.

    sted, utgiver, år, opplag, sider
    Springer Berlin/Heidelberg, 2013
    Serie
    Lecture Notes in Computer Science, ISSN 0302-9743 ; 7883
    HSV kategori
    Forskningsprogram
    Matematik med inriktning mot tillämpad matematik; Datoriserad bildanalys
    Identifikatorer
    urn:nbn:se:uu:diva-204715 (URN)10.1007/978-3-642-38294-9_16 (DOI)978-3-642-38293-2 (ISBN)
    Konferanse
    11th International Symposium on Mathematical Morphology
    Tilgjengelig fra: 2013-08-09 Laget: 2013-08-09 Sist oppdatert: 2014-04-29bibliografisk kontrollert
    7. Morphological image regularization using adaptive structuring functions
    Åpne denne publikasjonen i ny fane eller vindu >>Morphological image regularization using adaptive structuring functions
    (engelsk)Manuskript (preprint) (Annet vitenskapelig)
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-221161 (URN)
    Tilgjengelig fra: 2014-03-25 Laget: 2014-03-25 Sist oppdatert: 2014-04-29
    8. Adaptive Mathematical Morphology: a survey of the field
    Åpne denne publikasjonen i ny fane eller vindu >>Adaptive Mathematical Morphology: a survey of the field
    2014 (engelsk)Inngår i: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 47, s. 18-28Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    We present an up-to-date survey on the topic of adaptive mathematical morphology. A broad review of research performed within the field is provided, as well as an in-depth summary of the theoretical advances within the field. Adaptivity can come in many different ways, based on different attributes, measures, and parameters. Similarities and differences between a few selected methods for adaptive structuring elements are considered, providing perspective on the consequences of different types of adaptivity. We also provide a brief analysis of perspectives and trends within the field, discussing possible directions for future studies.

    Emneord
    Overview, Mathematical morphology, Adaptive morphology, Adaptive structuring elements, Adjunction property
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-221159 (URN)10.1016/j.patrec.2014.02.022 (DOI)000339999200003 ()
    Tilgjengelig fra: 2014-03-18 Laget: 2014-03-25 Sist oppdatert: 2018-01-11bibliografisk kontrollert
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