A genetic algorithm for geometric primitives extraction

This paper presents a geometric primitives extraction method from an image based on genetic algorithms. Our objective is to complete the classical Hough transform method which is a good extractor of segments from an image, since it isn´t adapted for the detection of three or higher primitive parameters in regard of the run time and the memory space used. The main idea of the proposed method consists to consider the primitive extraction as an optimization problem in the sense that the detection of the primitive is done by the minimization of the size and the position of the considered primitive in the parameters space. In order to deal with small primitives localization errors, we have used the distance image obtained with a particular morphological operator: the chamfer distance. Some results of geometric primitives extraction for both real and synthetic images are presented.