Title :
A genetic algorithm for the detection of 2D geometric primitives in images
Author :
Lutton, Evelyne ; Martinez, Patrzce
Author_Institution :
Inst. Nat. de Recherche en Inf. et Autom., Le Chesnay, France
Abstract :
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
Keywords :
feature extraction; 2D geometric primitives detection; Hough transform; genetic algorithm; image primitives extraction; Computational modeling; Genetic algorithms; Image edge detection; Image segmentation; Manufacturing; Optimization methods; Parameter estimation; Sampling methods; Simulated annealing; Stochastic processes;
Conference_Titel :
Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on
Conference_Location :
Jerusalem
Print_ISBN :
0-8186-6265-4
DOI :
10.1109/ICPR.1994.576345