Abstract
This paper describes a computational framework developed for the extraction of low-level directional primitives present in an image, and subsequent organization through a line segment detector. The system is divided in three stages: extraction of the directional features in the image through an efficient implementation of Gabor wavelet decomposition; reduction of these high dimensionality results by means of a growing cell structure; and extraction of the segments from the image. This last step was first implemented through a pseudo-color Fuzzy Hough Transform and then improved through some principles of the Burns segment detector.
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© 2005 Springer-Verlag Berlin Heidelberg
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Penas, M., Carreira, M.J., Penedo, M.G., Mariño, C. (2005). Segment Extraction Using Burns Principles in a Pseudo-color Fuzzy Hough Transform. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492542_22
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DOI: https://doi.org/10.1007/11492542_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26154-4
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