Comparison of alternative frameworks for directional primitive extraction

摘要

This paper describes and compares three alternative computational frameworks for the extraction of the directional primitives present in an image. These frameworks are based on Gabor decomposition, Sobel filtering, and filtering through the first derivative of a Gaussian filter, respectively. They are divided into two stages: low-level primitive extraction and organization of low-level primitives by means of dynamical neural networks. These alternative frameworks are compared and their relative advantages and disadvantages are outlined.