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. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Penas, M., Carreira, M. J., Penedo, M. G., & Mariño, C. (2005). Segment extraction using burns principles in a pseudo-color fuzzy Hough transform. In Lecture Notes in Computer Science (Vol. 3523, pp. 175–182). Springer Verlag. https://doi.org/10.1007/11492542_22
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