Title :
Genetic fusion: application to multi-components image segmentation
Author :
Rosenberger, C. ; Chehdi, K.
Author_Institution :
ENSSAT-LASTI, Lannion, France
Abstract :
In this communication, we propose a new approach which enables to fusion either the results of several segmentation methods of a same image or the different results in the case of a multi-components image. The developed method is based on a genetic algorithm approach which allows to combine segmentation results by taking into account their quality through an evaluation criterion. This criterion provides to quantify a segmentation result without any a priori knowledge such as the ground truth. This approach is applied to segment multi-components images by combining the segmentation results of each component. We show the efficiency of the method through some experimental results on several images
Keywords :
genetic algorithms; image segmentation; evaluation criterion; genetic algorithm approach; genetic fusion; multi-components image segmentation; Councils; Genetic algorithms; Genetic mutations; Image processing; Image segmentation; Merging; Pixel; Stability criteria;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on
Conference_Location :
Istanbul
Print_ISBN :
0-7803-6293-4
DOI :
10.1109/ICASSP.2000.859280