A genetic algorithm for the detection of 2D geometric primitives in images
Évelyne Lutton, Pablo Martı́nez · 2002
We investigate the use of genetic algorithms (GAs) for image primitives extraction (such as segments, circles, ellipses or quadrilaterals). This approach completes the well-known Hough transform, in the sense that GAs are efficient when the Hough approach becomes too expensive in memory, i.e. when we search for complex primitives having more than 3 or 4 parameters. A GA is a stochastic technique, relatively slow, but which provides with an efficient tool to search in a high dimensional space. The philosophy of the method is very similar to the Hough transform, which is to search an optimum in a parameter space. However, we will see that the implementation is different.