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.