| 1. |
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| 2. |
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| 3. |
- Andersson, Thord, et al.
(författare)
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WITAS Project at Computer Vision Laboratory; A status report (Jan 1998)
- 1998
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Ingår i: Proceedings of the SSAB symposium on image analysis. ; , s. 113-116
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Konferensbidrag (refereegranskat)abstract
- WITAS will be engaged in goal-directed basic research in the area of intelligent autonomous vehicles and other autonomous systems. In this paper an overview of the project is given together with a presentation of our research interests in the project. The current status of our part in the project is also given.
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| 4. |
- Bigun, Josef, et al.
(författare)
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Central Symmetry Modelling
- 1986
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Ingår i: Proceedings of EUSIPCO-86, Third European Signal Processing Conference. - Linköping : Linköping University Electronic Press. ; , s. 883-886
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Konferensbidrag (refereegranskat)abstract
- A definition of central symmetry for local neighborhoods of 2-D images is given. A complete ON-set of centrally symmetric basis functions is proposed. The local neighborhoods are expanded in this basis. The behavior of coefficient spectrum obtained by this expansion is proposed to be the foundation of central symmetry parameters of the neighbqrhoods. Specifically examination of two such behaviors are proposed: Point concentration and line concentration of the energy spectrum. Moreover, the study of these types of behaviors of the spectrum are shown to be possible to do in the spatial domain.
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| 5. |
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| 6. |
- Bigun, Josef, et al.
(författare)
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Multidimensional orientation estimation with applications to texture analysis and optical flow
- 1991
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Ingår i: IEEE Transactions on Pattern Analysis and Machine Intelligence. - : Institute of Electrical and Electronics Engineers (IEEE). - 0162-8828 .- 1939-3539. ; 13:8, s. 775-790
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Tidskriftsartikel (refereegranskat)abstract
- The problem of detection of orientation in finite dimensional Euclidean spaces is solved in the least squares sense. In particular, the theory is developed for the case when such orientation computations are necessary at all local neighborhoods of the n-dimensional Euclidean space. Detection of orientation is shown to correspond to fitting an axis or a plane to the Fourier transform of an n-dimensional structure. The solution of this problem is related to the solution of a well-known matrix eigenvalue problem. Moreover, it is shown that the necessary computations can be performed in the spatial domain without actually doing a Fourier transformation. Along with the orientation estimate, a certainty measure, based on the error of the fit, is proposed. Two applications in image analysis are considered: texture segmentation and optical flow. An implementation for 2-D (texture features) as well as 3-D (optical flow) is presented. In the case of 2-D, the method exploits the properties of the complex number field to by-pass the eigenvalue analysis, improving the speed and the numerical stability of the method. The theory is verified by experiments which confirm accurate orientation estimates and reliable certainty measures in the presence of noise. The comparative results indicate that the proposed theory produces algorithms computing robust texture features as well as optical flow. The computations are highly parallelizable and can be used in realtime image analysis since they utilize only elementary functions in a closed form (up to dimension 4) and Cartesian separable convolutions.
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| 7. |
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| 8. |
- Bigun, Josef, et al.
(författare)
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Optimal Orientation Detection of Linear Symmetry
- 1987
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Ingår i: Proceedings of the IEEE First International Conference on Computer Vision. - Linköping : Linköping University Electronic Press. ; , s. 433-438
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Konferensbidrag (refereegranskat)abstract
- The problem of optimal detection of orientation in arbitrary neighborhoods is solved in the least squares sense. It is shown that this corresponds to fitting an axis in the Fourier domain of the n-dimensional neighborhood, the solution of which is a well known solution of a matrix eigenvalue problem. The eigenvalues are the variance or inertia with respect to the axes given by their respective eigen vectors. The orientation is taken as the axis given by the least eigenvalue. Moreover it is shown that the necessary computations can be pursued in the spatial domain without doing a Fourier transformation. An implementation for 2-D is presented. Two certainty measures are given corresponding to the orientation estimate. These are the relative or the absolute distances between the two eigenvalues, revealing whether the fitted axis is much better than an axis orthogonal to it. The result of the implementation is verified by experiments which confirm an accurate orientation estimation and reliable certainty measure in the presence of additive noise at high level as well as low levels.
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| 9. |
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| 10. |
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| 11. |
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| 12. |
- Bårman, Håkan, et al.
(författare)
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Computer-Aided Analysis of Mammograms
- 1993
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Ingår i: Proceedings Nordic symposium on PACS, Digital Radiology and Telemedicine. ; , s. 76-
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Konferensbidrag (refereegranskat)
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| 13. |
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| 14. |
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| 15. |
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| 16. |
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| 17. |
- Bårman, Håkan, et al.
(författare)
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Feature Extraction for Computer-Aided Analysis of Mammograms
- 1994
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Ingår i: State of the Art in Digital Mammographic Image Analysis. - Singapore : World Scientific Publishing Co. Ltd. - 9810215096 - 9789810215095
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Bokkapitel (refereegranskat)abstract
- A framework for computer-aided analysis of mammograms is described. General computer vision algorithms are combined with application specific procedures in a hierarchical fashion. The system is under development and is currently limited to detection of a few types of suspicious areas. The image features are extracted by using feature extraction methods where wavelet techniques are utilized. A low-pass pyramid representation of the image is convolved with a number of quadrature filters. The filter outputs are combined according to simple local Fourier domain models into parameters describing the local neighborhood with respect to the model. This produces estimates for each pixel describing local size, orientation, Fourier phase, and shape with confidence measures associated to each parameter. Tentative object descriptions are then extracted from the pixel-based features by application-specific procedures with knowledge of relevant structures in mammograms. The orientation, relative brightness and shape of the object are obtained by selection of the pixel feature estimates which best describe the object. The list of object descriptions is examined by procedures, where each procedure corresponds to a specific type of suspicious area, e.g. clusters of microcalcifications.
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| 18. |
- Bårman, Håkan, et al.
(författare)
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Feature Extraction for Computer-Aided Analysis of Mammograms
- 1993
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Ingår i: International journal of pattern recognition and artificial intelligence. - 0218-0014. ; 7:6, s. 1339-1356
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Tidskriftsartikel (refereegranskat)abstract
- A framework for computer-aided analysis of mammograms is described. General computer vision algorithms are combined with application specific procedures in a hierarchical fashion. The system is under development and is currently limited to detection of a few types of suspicious areas. The image features are extracted by using feature extraction methods where wavelet techniques are utilized. A low-pass pyramid representation of the image is convolved with a number of quadrature filters. The filter outputs are combined according to simple local Fourier domain models into parameters describing the local neighborhood with respect to the model. This produces estimates for each pixel describing local size, orientation, Fourier phase, and shape with confidence measures associated to each parameter. Tentative object descriptions are then extracted from the pixel-based features by application-specific procedures with knowledge of relevant structures in mammograms. The orientation, relative brightness and shape of the object are obtained by selection of the pixel feature estimates which best describe the object. The list of object descriptions is examined by procedures, where each procedure corresponds to a specific type of suspicious area, e.g. clusters of microcalcifications.
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| 19. |
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| 20. |
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| 21. |
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| 22. |
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| 23. |
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| 24. |
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| 25. |
- Granlund, Gösta H.
(författare)
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A Nonlinear, Image-content Dependent Measure of Image Quality
- 1977
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In recent years, considerable research effort has been devoted to the development of useful descriptors for image quality. The attempts have been hampered by i n complete understanding of the operation of the human visual system. This has made it difficult to relate physical measures and perceptual traits.A new model for determination of image quality is proposed. Its main feature is that it tries to invoke image content into consideration. The model builds upon a theory of image linearization, which means that the information in an image can well enough be represented using linear segments or structures within local spatial regions and frequency ranges. This implies a l so a suggestion that information in an image has to do with one- dimensional correlations. This gives a possibility to separate image content from noise in images, and measure them both.Also a hypothesis is proposed that the visual system of humans does in fact perform such a linearization.
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| 26. |
- Granlund, Gösta H.
(författare)
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An Associative Perception-Action Structure using a Localized Space Variant Information Representation
- 2000
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Ingår i: Algebraic Frames for the Perception-Action Cycle. - Berlin, Heidelberg : Springer. - 3540410139 - 9783540410133 - 9783540452607 ; , s. 48-68
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Bokkapitel (refereegranskat)abstract
- Most of the processing in vision today uses spatially invariant operations. This gives efficient and compact computing structures, with the conventional convenient separation between data and operations. This also goes well with conventional Cartesian representation of data. Currently, there is a trend towards context dependent processing in various forms. This implies that operations will no longer be spatially invariant, but vary over the image dependent upon the image content. There are many ways in which such a contextual control can be implemented. Mechanisms can be added for the modification of operator behavior within the conventional computing structure. This has been done e.g. for the implementation of adaptive filtering. In order to obtain sufficient flexibility and power in the computing structure, it is necessary to go further than that. To achieve sufficiently good adaptivity, it is necessary to ensure that sufficiently complex control strategies can be represented. It is becoming increasingly apparent that this can not be achieved through prescription or program specification of rules. The reason being that these rules will be dauntingly complex and can not be be dealt with in sufficient detail. At the same time that we require the implementation of a spatially variant processing, this implies the requirement for a spatially variant information representation. Otherwise a sufficiently effective and flexible contextual control can not be implemented. This paper outlines a new structure for effective space variant processing. It utilises a new type of localized information representation, which can be viewed as outputs from band pass filters such as wavelets. A unique and important feature is that convex regions can be built up from a single layer of associating nodes. The specification of operations is made through learning or action controlled association.
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| 27. |
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| 28. |
- Granlund, Gösta H., et al.
(författare)
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Biological Vision
- 1995
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Ingår i: Signal Processing for Computer Vision. - Dordrecht : Kluwer. - 0792395301 - 9780792395300 ; , s. 41-95
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Bokkapitel (refereegranskat)abstract
- This chapter givesan overview of important biological vision mechanisms. Although agreat deal is known about neural processing of visual information,most essential questions about biological vision remain as yetunanswered. Nonetheless, the knowledge available has already provideduseful guidance to the organization of effective machine visionsystems.
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| 29. |
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| 30. |
- Granlund, Gösta H., et al.
(författare)
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Classification and Response Generation
- 1995
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Ingår i: Signal Processing for Computer Vision. - Dordrecht : Kluwer. - 0792395301 - 9780792395300 ; , s. 367-397
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Bokkapitel (refereegranskat)abstract
- This chapter is not original, but presents methods for linear classification in the tradition of N. J. Nilsson as well as R. O. Duda and P. E. Hart. Part of the motivation for including this well-known material is to allow the vision structure to be brought to a logical conclusion in which feature properties are combined to form responses or class statements. Another motivation developed here is to display the similarity in structure between convolution operations and linear discriminant functions. This brings all operations for feature extraction and classification to the use of a common component, linear discriminants. This is also illustrated in the form of perceptrons, which allows a transition to the modern theory of neural networks.
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| 31. |
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| 32. |
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| 33. |
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| 34. |
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| 35. |
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| 36. |
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| 37. |
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| 38. |
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| 39. |
- Granlund, Gösta H.
(författare)
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From Multidimensional Signals to the Generation of Responses
- 1997
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Ingår i: Algebraic Frames for the Perception-Action Cycle, eds G. Sommer and J. J. Koenderink. - : Springer-Verlag. ; , s. 29-53
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Konferensbidrag (refereegranskat)abstract
- It has become increasingly apparent that perception cannot be treated in isolation from the response generation, firstly because a very high degree of integration is required between different levels of percepts and corresponding response primitives. Secondly, it turns out that the response to be produced at a given instance is as much dependent upon the state of the system, as the percepts impinging upon the system. The state of the system is in consequence the combination of the responses produced and the percepts associated with these responses. Thirdly, it has become apparent that many classical aspects of perception, such as geometry, probably do not belong to the percept domain of a Vision system, but to the response domain. There are not yet solutions available to all of these problems. In consequence, this overview will focus on what are considered crucial problems for the future, rather than on the solutions available today. It will discuss hierarchical architectures for combination of percept and response primitives, and the concept of combined percept-response invariances as important structural elements for Vision. It will be maintained that learning is essential to obtain the necessary exibility and adaptivity. In consequence, it will be argued that invariances for the purpose of vision are not geometrical but derived from the percept-response interaction with the environment. The issue of information representation becomes extremely important in distributed structures of the types foreseen, where uncertainty of information has to be stated for update of models and associated data.
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| 40. |
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| 41. |
- Granlund, Gösta H., et al.
(författare)
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GOP, A Paradigm in Hierarchical Image Processing
- 1982
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Ingår i: Proceedings of The First IEEE Computer Society International Symposium on Medical Imaging and Image Interpretation, ISMI II'82.
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Konferensbidrag (refereegranskat)
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| 42. |
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| 43. |
- Granlund, Gösta H.
(författare)
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Hierarchical Image Processing
- 1983
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Ingår i: Proceedings of SPIE Technical Conference.
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Konferensbidrag (refereegranskat)
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| 44. |
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| 45. |
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| 46. |
- Granlund, Gösta H., et al.
(författare)
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Image Enhancement
- 1983
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Ingår i: Fundamentals in Computer Vision. - Cambridge : Cambridge University Press. - 0521250994 ; , s. 57-68
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Bokkapitel (refereegranskat)
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| 47. |
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| 48. |
- Granlund, Gösta H.
(författare)
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Image Sequence Analysis
- 1993
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Ingår i: Mustererkennung 1993, Mustererkennung im Dienste der Gesundheit eds S.J. Pöppl and H. Handels. ; , s. 1-18
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Konferensbidrag (refereegranskat)
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| 49. |
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| 50. |
- Granlund, Gösta H.
(författare)
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In Search of a General Picture Processing Operator
- 1978
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Ingår i: Computer Graphics and Image Processing. - : Elsevier. - 0146-664X. ; 8:2, s. 155-173
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Tidskriftsartikel (refereegranskat)abstract
- The problem of finding a general, parallel, and hierarchical operator for picture processing is considered. An operator is defined which at different levels can detect and describe structure as opposed to uniformity within local regions, whatever structure and uniformity may imply at a particular level. The operator performs a mapping from one complex field to another. The important characteristic of this approach is the use of complex fields which allows a global-to-local feedback. In the transformation process the image is simplified. A Fourier implementation of the operator is described and a new transform is defined. The operators become increasingly global on higher levels in order to include adjacent high-level features. A hierarchical structure of such transformations gives a sequential description of structure over increasingly larger regions of the image. The processed information at different levels can be used as input to a classifier. Examples are given of processing results.
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