Abstract
This paper describes a computational framework developed for the extraction of low-level directional primitives present in an image, and subsequent organization using the laws of perceptual grouping. The system is divided in two stages. The first one consists on the extraction of the direction of pixels in the image, through an efficient implementation of Gabor wavelet decomposition. The second one consists on the reduction of these high dimensionality results by means of an auto-organized structure. For this second stage, three different auto-organized structures have been studied: self-organized maps (SOM), growing cell structures (GCS) and growing neural gas (GNG). Results have showed that GCS is the most appropriate structure in the context of this work.
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© 2003 Springer-Verlag Berlin Heidelberg
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Penas, M., Carreira, M.J., Penedo, M.G. (2003). Gabor Wavelets and Auto-organised Structures for Directional Primitive Extraction. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_84
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DOI: https://doi.org/10.1007/978-3-540-44871-6_84
Publisher Name: Springer, Berlin, Heidelberg
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