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Deterministic Defuzzification based on Spectral Projected Gradient Optimization
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- Lukic, Tibor (author)
- University of Novi Sad, Faculty of Engineering
-
- Sladoje, Natasa (author)
- University of Novi Sad, Faculty of Engineering
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- Lindblad, Joakim (author)
- Uppsala universitet,Centrum för bildanalys,Datoriserad bildanalys
- (creator_code:org_t)
- Berlin / Heidelberg : Springer, 2008
- 2008
- English.
- In: 30th Symposium of the German Association for Pattern Recognition (DAGM). - Berlin / Heidelberg : Springer. - 9783540693208 ; , s. 476-485
- Conference paper (peer-reviewed)
Abstract
Subject headings
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- We apply deterministic optimization based on Spectral Projected Gradient method in combination with concave regularization to solve the minimization problem imposed by defuzzification by feature distance minimization. We compare the performance of the proposed algorithm with the methods previously recommended for the same task, (non-deterministic) simulated annealing and (deterministic) DC based algorithm. The evaluation, including numerical tests performed on synthetic and real images, shows advantages of the new method in terms of speed and flexibility regarding inclusion of additional features in defuzzification. Its relatively low memory requirements allow the application of the suggested method for defuzzification of 3D objects.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
Keyword
- Image analysis
- Bildanalys
Publication and Content Type
- ref (subject category)
- kon (subject category)
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