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  • 201.
    Hamid Muhammed, Hamed
    Uppsala University, Interfaculty Units, Centre for Image Analysis.
    Feature Vector Based Analysis: A Unified Concept for Multivariate Image Analysis2001In: Proceedings of Irish Machine Vision and Image Processing Conference, p. 219-226Article in journal (Refereed)
  • 202.
    Hamid Muhammed, Hamed
    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.
    Hyperspectral Crop Reflectance Data for characterising and estimating Fungal Disease Severity in Wheat2005In: Biosystems Engineering, Vol. 91, no 1, p. 9-20Article in journal (Refereed)
  • 203.
    Hamid Muhammed, Hamed
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Hyperspectral Crop Reflectance Data for characterising and estimating Fungal Disease Severity in Wheat2005In: Biosystems Engineering, Vol. 91, no 1, p. 9-20Article in journal (Other (popular scientific, debate etc.))
    Abstract [en]

    Many studies have shown the usefulness of hyperspectral crop reflectance data for detecting plant pathological stress. However, there is still a need to identify unique signatures for specific stresses amidst the constantly changing background associated with normal crop growth and development. Comparing spatial and temporal patterns in crop spectra can provide such signatures. This work was concerned with characterising and estimating fungal disease severity in a spring wheat crop. This goal can be accomplished by using a reference data set consisting of hyperspectral crop reflectance data vectors and the corresponding disease severity field assessments. The hyperspectral vectors were first normalised into zero-mean and unit-variance vectors by performing various combinations of spectral- and band-wise normalisations. Then, after applying the same normalisation procedures to the new hyperspectral data, a nearest-neighbour classifier was used to classify the new data against the reference data. Finally, the corresponding stress signatures were computed using a linear transformation model. High correlation was obtained between the classification results and the corresponding field assessments of fungal disease severity, confirming the usefulness and efficiency of this approach. The effects of increased disease severity could be characterised by analysing the resulting disease signatures obtained when applying the different normalisation procedures. The low computational load of this approach makes it suitable for real-time on-vehicle applications.

  • 204.
    Hamid Muhammed, Hamed
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Hyperspectral Image Generation, Processing and Analysis2005Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Hyperspectral reflectance data are utilised in many applications, where measured data are processed and converted into physical, chemical and/or biological properties of the target objects and/or processes being studied. It has been proven that crop reflectance data can be used to detect, characterise and quantify disease severity and plant density.

    In this thesis, various methods were proposed and used for detection, characterisation and quantification of disease severity and plant density utilising data acquired by hand-held spectrometers. Following this direction, hyperspectral images provide both spatial and spectral information opening for more efficient analysis.

    Hence, in this thesis, various surface water quality parameters of inland waters have been monitored using hyperspectral images acquired by airborne systems. After processing the images to obtain ground reflectance data, the analysis was performed using similar methods to those of the previous case. Hence, these methods may also find application in future satellite based hyperspectral imaging systems.

    However, the large size of these images raises the need for efficient data reduction. Self organising and learning neural networks, that can follow and preserve the topology of the data, have been shown to be efficient for data reduction. More advanced variants of these neural networks, referred to as the weighted neural networks (WNN), were proposed in this thesis, such as the weighted incremental neural network (WINN), which can be used for efficient reduction, mapping and clustering of large high-dimensional data sets, such as hyperspectral images.

    Finally, the analysis can be reversed to generate spectra from simpler measurements using multiple colour-filter mosaics, as suggested in the thesis. The acquired instantaneous single image, including the mosaic effects, is demosaicked to generate a multi-band image that can finally be transformed into a hyperspectral image.

    List of papers
    1. Sensitivity analysis of multi-channel images intended for spectrometry applications
    Open this publication in new window or tab >>Sensitivity analysis of multi-channel images intended for spectrometry applications
    (English)Article in journal (Refereed) Submitted
    Identifiers
    urn:nbn:se:uu:diva-93367 (URN)
    Available from: 2005-09-05 Created: 2005-09-05 Last updated: 2010-03-01Bibliographically approved
    2. Using Multiple Colour Mosaics for Multi- and Hyperspectral Imaging
    Open this publication in new window or tab >>Using Multiple Colour Mosaics for Multi- and Hyperspectral Imaging
    (English)Article in journal (Refereed) Submitted
    Identifiers
    urn:nbn:se:uu:diva-93368 (URN)
    Available from: 2005-09-05 Created: 2005-09-05 Last updated: 2010-03-01Bibliographically approved
    3. New approaches for surface water quality estimation in Lake Erken, Sweden, using remotely sensed hyperspectral data
    Open this publication in new window or tab >>New approaches for surface water quality estimation in Lake Erken, Sweden, using remotely sensed hyperspectral data
    (English)Article in journal (Refereed) Submitted
    Identifiers
    urn:nbn:se:uu:diva-93369 (URN)
    Available from: 2005-09-05 Created: 2005-09-05 Last updated: 2010-03-01Bibliographically approved
    4. Industrial plume detection by employing spectral descriptive signatures for anomaly detection
    Open this publication in new window or tab >>Industrial plume detection by employing spectral descriptive signatures for anomaly detection
    (English)Article in journal (Refereed) Submitted
    Identifiers
    urn:nbn:se:uu:diva-93370 (URN)
    Available from: 2005-09-05 Created: 2005-09-05 Last updated: 2010-03-01Bibliographically approved
    5. Using Feature Vector Based Analysis, based on Principal Component Analysis and Independent Component Analysis, for Analysing Hyperspectral Images
    Open this publication in new window or tab >>Using Feature Vector Based Analysis, based on Principal Component Analysis and Independent Component Analysis, for Analysing Hyperspectral Images
    2001 In: Proceedings of 11th International Conference for Image Analysis and Processing, p. 309-315Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-93371 (URN)
    Available from: 2005-09-05 Created: 2005-09-05Bibliographically approved
    6. Feature Vector Based Analysis: A Unified Concept for Multivariate Image Analysis
    Open this publication in new window or tab >>Feature Vector Based Analysis: A Unified Concept for Multivariate Image Analysis
    2001 In: Proceedings of Irish Machine Vision and Image Processing Conference, p. 219-226Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-93372 (URN)
    Available from: 2005-09-05 Created: 2005-09-05Bibliographically approved
    7. Feature Vector Based Analysis of Hyperspectral Crop Reflectance Data for Discrimination and Quantification of Fungal Disease Severity in Wheat
    Open this publication in new window or tab >>Feature Vector Based Analysis of Hyperspectral Crop Reflectance Data for Discrimination and Quantification of Fungal Disease Severity in Wheat
    2003 (English)In: Biosystems Engineering, Vol. 86, no 2, p. 125-134Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-93373 (URN)
    Available from: 2005-09-05 Created: 2005-09-05 Last updated: 2010-03-01Bibliographically approved
    8. Hyperspectral Crop Reflectance Data for characterising and estimating Fungal Disease Severity in Wheat
    Open this publication in new window or tab >>Hyperspectral Crop Reflectance Data for characterising and estimating Fungal Disease Severity in Wheat
    2005 (English)In: Biosystems Engineering, Vol. 91, no 1, p. 9-20Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-93374 (URN)
    Available from: 2005-09-05 Created: 2005-09-05 Last updated: 2010-03-01Bibliographically approved
    9. Measuring crop status using multivariate analysis of hyperspectral field reflectance with application on disease severity and amount of plant density
    Open this publication in new window or tab >>Measuring crop status using multivariate analysis of hyperspectral field reflectance with application on disease severity and amount of plant density
    2005 (English)In: Proceedings of 5th European Conference on Precision Agriculture, Vol. Precision Agriculture ’05, p. 217-225Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-93375 (URN)
    Available from: 2005-09-05 Created: 2005-09-05 Last updated: 2010-03-01Bibliographically approved
    10. Using Weighted Fixed Neural Networks for Unsupervised Fuzzy Clustering
    Open this publication in new window or tab >>Using Weighted Fixed Neural Networks for Unsupervised Fuzzy Clustering
    2002 (English)In: International Journal of Neural Systems, Vol. 12, no 6, p. 425-434Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-93376 (URN)
    Available from: 2005-09-05 Created: 2005-09-05 Last updated: 2010-03-01Bibliographically approved
    11. Unsupervised Fuzzy Clustering Using Weighted Incremental Neural Networks
    Open this publication in new window or tab >>Unsupervised Fuzzy Clustering Using Weighted Incremental Neural Networks
    2004 (English)In: International Journal of Neural Systems, Vol. 14, no 6, p. 355-371Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-93377 (URN)
    Available from: 2005-09-05 Created: 2005-09-05 Last updated: 2010-03-01Bibliographically approved
    12. Unsupervised Fuzzy Clustering and Image Segmentation Using Weighted Neural Networks
    Open this publication in new window or tab >>Unsupervised Fuzzy Clustering and Image Segmentation Using Weighted Neural Networks
    2003 (English)In: Proceedings of 12th International Conference for Image Analysis and Processing, p. 308-313Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-93378 (URN)
    Available from: 2005-09-05 Created: 2005-09-05 Last updated: 2010-03-01Bibliographically approved
    13. Unsupervised Hyperspectral Image Segmentation Using a New Class of Neuro-Fuzzy Systems Based on Weighted Incremental Neural Networks
    Open this publication in new window or tab >>Unsupervised Hyperspectral Image Segmentation Using a New Class of Neuro-Fuzzy Systems Based on Weighted Incremental Neural Networks
    2002 (English)In: 31st Applied Imagery Pattern Recognition Worshop (AIPR 2002), Washington DC, USA, 2002Conference paper, Published paper (Other scientific)
    Abstract [en]

    Segmenting hyperspectral images is an important task for simplifying the

    Keywords
    Hyperspectral images, Unsupervised Image Segmentation, Unsupervised Fuzzy Clustering, Neuro-Fuzzy Systems, Weighted IncrementalNeural Network (WINN), Watersheds.
    National Category
    Computer Vision and Robotics (Autonomous Systems)
    Identifiers
    urn:nbn:se:uu:diva-42446 (URN)
    Available from: 2005-08-25 Created: 2005-08-25 Last updated: 2018-01-11
    14. A Comparison of Neuro-Fuzzy and Traditional Image Segmentation Methods for Automated Detection of Buildings in Aerial Photos
    Open this publication in new window or tab >>A Comparison of Neuro-Fuzzy and Traditional Image Segmentation Methods for Automated Detection of Buildings in Aerial Photos
    2002 (English)In: Proceedings of PCV'02: PHOTOGRAMMETRIC COMPUTER VISION 2002Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-93380 (URN)
    Available from: 2005-09-05 Created: 2005-09-05 Last updated: 2010-03-01Bibliographically approved
  • 205.
    Hamid Muhammed, Hamed
    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.
    Industrial plume detection by employing spectral descriptive signatures for anomaly detectionArticle in journal (Refereed)
  • 206.
    Hamid Muhammed, Hamed
    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.
    New approaches for surface water quality estimation in Lake Erken, Sweden, using remotely sensed hyperspectral dataArticle in journal (Refereed)
  • 207.
    Hamid Muhammed, Hamed
    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.
    Unsupervised Fuzzy Clustering and Image Segmentation Using Weighted Neural Networks2003In: Proceedings of 12th International Conference for Image Analysis and Processing, p. 308-313Article in journal (Refereed)
  • 208.
    Hamid Muhammed, Hamed
    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.
    Unsupervised Fuzzy Clustering Using Weighted Incremental Neural Networks2004In: International Journal of Neural Systems, Vol. 14, no 6, p. 355-371Article in journal (Refereed)
  • 209.
    Hamid Muhammed, Hamed
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Unsupervised Fuzzy Clustering Using Weighted Incremental Neural Networks2004In: International Journal of Neural Systems (IJNS), Vol. 14, no 6, p. 355-371Article in journal (Refereed)
    Abstract [en]

    A new more efficient variant of a recently developed algorithm for unsupervised fuzzy clustering is introduced. A Weighted Incremental Neural Network (WINN) is introduced and used for this purpose. The new approach is called FC-WINN (Fuzzy Clustering using WINN). The WINN algorithm produces a net of nodes connected by edges, which reflects and preserves the topology of the input data set. Additional weights, which are proportional to the local densities in input space, are associated with the resulting nodes and edges to store useful information bout the topological relations in the given input data set. A fuzziness factor, proportional to the connectedness of the net, is introduced in the system. A watershed-like procedure is used to cluster the resulting net. The number of the resulting clusters is determined by this procedure. Only two parameters must be chosen by the user for the FC-WINN algorithm to determine the resolution and the connectedness of the net. Other parameters that must be specified are those which are necessary for the used incremental neural network, which is a modified version of the Growing Neural Gas algorithm (GNG). The FC-WINN algorithm is computationally efficient when compared to other approaches for clustering large high-dimensional data sets.

  • 210.
    Hamid Muhammed, Hamed
    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.
    Using Multiple Colour Mosaics for Multi- and Hyperspectral ImagingArticle in journal (Refereed)
  • 211.
    Hamid Muhammed, Hamed
    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.
    Using Weighted Fixed Neural Networks for Unsupervised Fuzzy Clustering2002In: International Journal of Neural Systems, Vol. 12, no 6, p. 425-434Article in journal (Refereed)
  • 212.
    Hamid Muhammed, Hamed
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis.
    Ammenberg, Petra
    Bengtsson, Ewert
    Using Feature Vector Based Analysis, based on Principal Component Analysis and Independent Component Analysis, for Analysing Hyperspectral Images2001In: Proceedings of 11th International Conference for Image Analysis and Processing, p. 309-315Article in journal (Refereed)
  • 213.
    Hamid Muhammed, Hamed
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Bergholm, Fredrik
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Camera-spectrometer for instantaneous multi- and hyperspectral imaging2005In: 5th European Conference on Precision Agriculture, 2005, p. 1008-Conference paper (Other scientific)
    Abstract [en]

    The most serious limitation of conventional multi- and hyperspectral imagery systems is the need for scanning time to be able to acquire the whole image cube, which contains huge amount of data needing large memory-capacity and giving rise to another serious limitation of these systems. In this work, a novel cost-effective technique, that solves the problems mentioned above, is presented. The system has no moving parts and the whole multi- or hyperspectral image cube is acquired instantaneously, making it ready to record multi- and hyperspectral digital video.

  • 214.
    Hamid Muhammed, Hamed
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Bergholm, Fredrik
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Camera-spectrometer for multi- and hyperspectral imaging2005In: Swedish Society for Automated Image Analysis Symposium - SSBA 2005, 2005, p. 45-48Conference paper (Other scientific)
    Abstract [en]

    This paper presents a novel approach for modifying an

    ordinary digital camera to be able to generate multior

    hyperspectral images. The basic idea is to use

    miniature (spatially and spectrally) overlapping colormosaic

    filters with a spatial resolution which is as

    close as possible to the actual resolution of the sensor

    plate. What is new here is that common (cheap)

    printing techniques can be used to produce these filter

    mosaics. The resulting image which shows locally

    filtered scene areas, can be transformed into a

    hyperspectral image by considering each group of

    neighboring pixels and transforming it into a single

    image element in the final hyperspectral image.

  • 215.
    Hamid Muhammed, Hamed
    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.
    Bergholm, Fredrik
    Sensitivity analysis of multi-channel images intended for spectrometry applicationsArticle in journal (Refereed)
  • 216.
    Hamid Muhammed, Hamed
    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.
    Larsolle, Anders
    Feature Vector Based Analysis of Hyperspectral Crop Reflectance Data for Discrimination and Quantification of Fungal Disease Severity in Wheat2003In: Biosystems Engineering, Vol. 86, no 2, p. 125-134Article in journal (Refereed)
  • 217.
    Hast, A.
    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, T.
    Bengtsson, E.
    Approximated Phong Shading by using the Euler Method2001Conference paper (Refereed)
    Abstract [en]

    After almost three decades and several improvements, Gouraud shading is still

  • 218.
    Hast, A.
    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, T.
    Bengtsson, E.
    Improved Shading Performance by Avoiding Vector Normalization2001In: Conference for Promotion of Research in IT at New Universities and at University Colleges in Sweden, 2001, p. 73-85Conference paper (Other scientific)
  • 219. Hast, A
    et al.
    Wesslén, Daniel
    Seipel, Stefan
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Automatic control. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Människa-datorinteraktion.
    Improved Diffuse Anisotropic Shading2004In: Sigrad Conference 2004, 2004, p. 57-58Conference paper (Other scientific)
  • 220.
    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.))
  • 221.
    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.
    Europar 2010, Parallel Processing Workshops: UCHPC2010.2010Conference proceedings (editor) (Refereed)
  • 222.
    Hast, Anders
    Uppsala University, Interfaculty Units, Centre for Image Analysis.
    Improved Algorithms for Fast Shading and Lighting2004Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Shading is a technique that is used in computer graphics to make faceted objects appear smooth and more realistic. In the research presented in this thesis we have investigated how shading can be generated as efficiently as possible without sacrificing quality.

    In the classical approach to high quality shading proposed by Phong, the illumination equation is computed per pixel using an interpolated normal. The normals at the vertices are bi-linearly interpolated over the polygon to obtain a normal per pixel. Correct shading requires normalization of these normals, which is computationally demanding involving a square root. In our research we have shown how this normalization can be eliminated through the use of spherical interpolation and the Chebyshev recurrence formula, reducing the calculation to a few single arithmetic operations per pixel.

    Still a substantial setup operation is needed for each scanline. We have studied how also this can be made more efficient, with some limited progress so far. An alternative approach is to do the most of the setup on polygon level and incrementally compute the setup needed per scanline. In particular, we have studied quadratic shading approaches, i.e. fitting second degree surfaces to the polygons. The most successful approach has been through what we have called X-shading, where the setup is calculated by using an efficient approximation for the mid-edge normals. This setup is about four times faster than previously known methods.

    In the process of studying shading methods we have also made some contributions to improving bump-mapping and simulation of different kinds of light sources.

    The developed methods will be of interest in future generations of computer graphics software and hardware systems, ranging from high end systems to generate realistic movies and 3D games, to handheld devices such as mobile phones with graphics displays.

    List of papers
    1. Improved Shading Performance by avoiding Vector Normalization
    Open this publication in new window or tab >>Improved Shading Performance by avoiding Vector Normalization
    2001 (English)In: WSCG01, p. 1-8Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-91510 (URN)
    Available from: 2004-04-06 Created: 2004-04-06 Last updated: 2010-03-01Bibliographically approved
    2. Approximated Phong Shading by using the Euler Method
    Open this publication in new window or tab >>Approximated Phong Shading by using the Euler Method
    2001 (English)In: Eurographics01, p. 43-48Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-91511 (URN)
    Available from: 2004-04-06 Created: 2004-04-06 Last updated: 2010-03-01Bibliographically approved
    3. Shading by Spherical Linear Interpolation using De Moivre's Formula
    Open this publication in new window or tab >>Shading by Spherical Linear Interpolation using De Moivre's Formula
    2003 (English)In: WSCG03, p. 57-60Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-91512 (URN)
    Available from: 2004-04-06 Created: 2004-04-06 Last updated: 2010-03-01Bibliographically approved
    4. Faster shading by equal angle interpolation of vectors
    Open this publication in new window or tab >>Faster shading by equal angle interpolation of vectors
    2004 (English)In: IEEE Transactions on Visualization and Computer Graphics, p. 217-223Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-91513 (URN)
    Available from: 2004-04-06 Created: 2004-04-06 Last updated: 2010-03-01Bibliographically approved
    5. Faster Computer Graphics - by Reformulation and Simplification of Mathematical Formulas and Algorithms
    Open this publication in new window or tab >>Faster Computer Graphics - by Reformulation and Simplification of Mathematical Formulas and Algorithms
    2001 (English)In: IMAGINE2001Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-91514 (URN)
    Available from: 2004-04-06 Created: 2004-04-06 Last updated: 2010-03-01Bibliographically approved
    6. Improved Bump Mapping by using Quadratic Vector Interpolation
    Open this publication in new window or tab >>Improved Bump Mapping by using Quadratic Vector Interpolation
    2002 (English)In: Eurographics02Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-91515 (URN)
    Available from: 2004-04-06 Created: 2004-04-06 Last updated: 2010-03-01Bibliographically approved
    7. Surface Construction with Near Least Square Acceleration based on Vertex Normals on Triangular Meshes
    Open this publication in new window or tab >>Surface Construction with Near Least Square Acceleration based on Vertex Normals on Triangular Meshes
    2002 (English)In: Sigrad, p. 43-48Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-91516 (URN)
    Available from: 2004-04-06 Created: 2004-04-06 Last updated: 2010-03-01Bibliographically approved
    8. Fast Quadratic Shading by using a Mid-edge Vector Approximation
    Open this publication in new window or tab >>Fast Quadratic Shading by using a Mid-edge Vector Approximation
    (English)Article in journal (Refereed) Submitted
    Identifiers
    urn:nbn:se:uu:diva-91517 (URN)
    Available from: 2004-04-06 Created: 2004-04-06 Last updated: 2010-03-01Bibliographically approved
    9. Reconstruction Filters for Bump Mapping
    Open this publication in new window or tab >>Reconstruction Filters for Bump Mapping
    2002 (English)In: WSCG02, p. 9-12Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-91518 (URN)
    Available from: 2004-04-06 Created: 2004-04-06 Last updated: 2010-03-01Bibliographically approved
    10. Soft and Hard Edged Spotlights
    Open this publication in new window or tab >>Soft and Hard Edged Spotlights
    2004 (English)In: WSCG04, p. 95-99Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-91519 (URN)
    Available from: 2004-04-06 Created: 2004-04-06 Last updated: 2010-03-01Bibliographically approved
    11. Fast Specular Highlights by modifying the Phong-Blinn Model
    Open this publication in new window or tab >>Fast Specular Highlights by modifying the Phong-Blinn Model
    2003 (English)In: SIGGRAPH03Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-91520 (URN)
    Available from: 2004-04-06 Created: 2004-04-06 Last updated: 2010-03-01Bibliographically approved
  • 223.
    Hast, Anders
    Uppsala University, Interfaculty Units, Centre for Image Analysis.
    Improved Fundamental Algorithms for Fast Computer Graphics2002Licentiate thesis, monograph (Other scientific)
  • 224.
    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.
    Shading by Quaternion Interpolation2005In: WSCG2005, 2005, p. 53-56Conference paper (Refereed)
    Abstract [en]

    The purpose of this paper is to show that linear interpolation of quaternions can be used for true Phong shading and also for related techniques that use frames, like bump mapping and anisotropic shading. Quaternion interpolation for shading has not been proposed in literature and the reason might be that it turns out to be mostly

    of academic interest, and it will here be explained why. Furthermore some pros and cons of interpolation using quaternions will be discussed. The effect of using this approach is that the square root in the normalization process disappears. The square root is now implemented in modern graphics hardware in such way that it is very fast. However for other types of platforms, especially hand held devices, the square root is computationally expensive and any software algorithm that could produce true Phong shading without the square root might turn out to be useful. It will be shown that linear interpolation of quaternion could be useful for bump mapping as well. However, quaternion arithmetic operations are not implemented in modern graphics hardware, and are therefore not useful until this is done.

  • 225.
    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)
  • 226.
    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)
  • 227.
    Hast Anders, 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 ntialiasing for bump maps and a fast normalization trick2003Chapter in book (Refereed)
  • 228.
    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
    Approximated Phong Shading by using the Euler Method2001In: Eurographics01, p. 43-48Article in journal (Refereed)
  • 229.
    Hast Anders, 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.
    Fast setup for bilinear and biquadratic interpolation over triangles2003Chapter in book (Refereed)
  • 230.
    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
    Fast Specular Highlights by modifying the Phong-Blinn Model2003In: SIGGRAPH03Article in journal (Refereed)
  • 231.
    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
    Faster Computer Graphics - by Reformulation and Simplification of Mathematical Formulas and Algorithms2001In: IMAGINE2001Article in journal (Refereed)
  • 232.
    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
    Improved Bump Mapping by using Quadratic Vector Interpolation2002In: Eurographics02Article in journal (Refereed)
  • 233.
    Hast Anders, 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.
    Improved Bump Mapping by using Quadratic Vector Interpolation2002Conference paper (Refereed)
  • 234.
    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
    Improved Shading Performance by avoiding Vector Normalization2001In: WSCG01, p. 1-8Article in journal (Refereed)
  • 235.
    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.

  • 236.
    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
    Reconstruction Filters for Bump Mapping2002In: WSCG02, p. 9-12Article in journal (Refereed)
  • 237.
    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)
  • 238.
    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
    Shading by Spherical Linear Interpolation using De Moivre's Formula2003In: WSCG03, p. 57-60Article in journal (Refereed)
  • 239.
    Hast, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for 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.
    Soft and Hard Edged Spotlights2004In: WSCG04, p. 95-99Article in journal (Refereed)
  • 240.
    Hedrich, Jens
    et al.
    Institute for computer visualisation, University of Koblenz-Landau, Germany.
    Paulus, Dietrich
    Institute for computer visualisation, University of Koblenz-Landau, Germany.
    Mäkeler, Hendrik
    Uppsala University, Music and Museums, Uppsala University Museum, Uppsala University Coin Cabinet.
    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.
    Image-based comparison of pre-modern coins and medals2010In: 16 Workshop Farbbildverarbeitung, 2010, p. 156-169Conference paper (Other academic)
  • 241.
    Hellström, M
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Ranefall, Petter
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Wester, K
    Brändstedt, S
    Busch, Christer
    Effect of androgen deprivation on epithelial and mesenchymal tissue components in localized prostate cancer1997In: British Journal of Urology, ISSN 0007-1331, E-ISSN 1365-2176, Vol. 79, no 3, p. 421-426Article in journal (Refereed)
    Abstract [en]

    Objective To measure the area distribution of epithelial and mesenchymal components in the prostate of patients with localized prostate cancer after temporary androgen deprivation. Patients and methods Surgical specimens from 38 patients treated with the

  • 242. Henriksson, Karin M.
    et al.
    Kelly, Brendan D.
    Lane, Abble
    Hult, Roger
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    McNeil, Thomas F.
    Agartz, Ingrid
    A morphometric magnetic resonance method for measuring cranial, facial and brain characteristics for application to schizophrenia: Part 12006In: Psychiatry Research: Neuroimaging, ISSN 0925-4927, E-ISSN 1872-7506, Vol. 147, no 2-3, p. 173-186Article in journal (Refereed)
    Abstract [en]

    Serious psychopathology in adulthood may be associated with disturbed foetal brain development, which potentially shows lingering "fossil marks" in the cranial and facial regions. Several methods exist for assessing external craniofacial and internal brain distances but, to our knowledge, no method yet provides simultaneous measurement of cranial, facial and brain dimensions in live subjects. In this article we describe a method to identify landmarks on magnetic resonance images (MRI) for simultaneous measurement of cranial, facial and brain characteristics potentially associated with psychosis. To test the method itself, 30 patients with chronic schizophrenia and 31 healthy comparison subjects, mean age 41 years, were randomly selected from a larger cohort recruited at the Karolinska Hospital, Sweden. Participants were investigated with MRI, and 60 landmarks in the cranial, facial and brain regions were identified in the images. An independent anthropometric examination measured external craniofacial characteristics for study in relation to measurements produced through MRI. High inter-scorer and re-test reliabilities were obtained for two independent scorers of the landmarks in the MR images. Measurements of potentially comparable craniofacial distances showed high alignment with an established anthropometric method. This new method can provide simultaneous investigation of multiple aspects of cranial, facial and brain morphology in MR images originally collected for other purposes. In a second article we will use this method to compare 3D craniofacial measurements and shape between schizophrenia patients and healthy controls.

  • 243.
    Holmberg, Björn
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Nordin, Bo
    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.
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Lanshammar, Håkan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Estimating human limb motion using skin texture as virtual markers2008Manuscript (preprint) (Other academic)
  • 244.
    Holmberg, Björn
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Nordin, Bo
    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, Automatic control.
    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, Automatic control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Lanshammar, Håkan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
    Possibilities in using skin texture based image registration for movement analysis2006In: Ninth International Symposium On the 3D Analysis of Human Motion, 2006Conference paper (Refereed)
  • 245.
    Holting, Per
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Wählby, Carolina
    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.
    Easy-to-use object selection by color space projections and watershed segmentation2005In: Image Analysis and Processing: ICIAP 2005 13th International Conference, Cagliari, Italy, September 6-8, 2005. Proceedings, 2005, p. 269-276Conference paper (Refereed)
    Abstract [en]

    Digital cameras are gaining in popularity, and not only experts in image analysis, but also the average users, show a growing interest in image processing. Many different kinds of software for image processing offer tools for object selection, or segmentation, but most of them require expertise knowledge, or leave too little freedom in expressing the desired segmentation. This paper presents an easy to use tool for object segmentation in color images. The amount of user interaction is minimized, and no tuning parameters are needed. The method is based on the watershed segmentation algorithm, combined with seeding information given by the user, and color space projections for optimized object edge detection. The presented method can successfully segment objects in most types of color images.

  • 246.
    Homman M., Sintorn I., Hultenby K., Borgefors G., Söderberg-Naucler C.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Nuclear egress of human Cytomegalovirus capsids by budding through thenuclear membrane,2002In: Proc. Int. Conf. on Electron Microscopy, Durban, South Africa, 2002., 2002Conference paper (Other scientific)
  • 247.
    Hullberg, A.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Ballerini, L.
    Determination of holes and cracks in meat with image analysis2002In: 48th International Congress of Meat Science and Technology, Rome, Italy, 25-30 August 2002, 2002, p. 336-337Conference paper (Other scientific)
  • 248.
    Hult, R.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Grey-Level Morphology Based Segmentation of Cortex2001In: Swedish Society for Automated Image Analysis Symposium - SSAB 2001,ITN, Campus Norrköping, LinköpingUniversity, 2001, p. 151-154Conference paper (Other scientific)
  • 249.
    Hult, R.
    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.
    Grey-level Morphology Based Segmentation of MRI of the Human Cortex2001In: Proceedings of ICIAP’01 11th International Conference on Image Analysis and Processing, Palermo, Italy, 2001, p. 578–583-Chapter in book (Other academic)
  • 250.
    Hult, R
    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.
    Grey-level Morphology Combined with an Artificial Networks Approach for Multimodal Segmentation of the HippocampusIn: Proceedings of ICIAP’03 12th International Conference on ImageChapter in book (Other academic)
2345678 201 - 250 of 683
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