关键词: YCbCr空间, 遗传算法（GA）, 棉花, 图像分割

Abstract: Cotton segmentation is the key step of cotton picking robot vision system. The accurate and effective segmentation of cotton is useful to its position in three-dimensional space while cotton is in bright light or shadow complex field environment. It can get fitness function by training BP neural network and its output error, and then use selection, crossover and mutation operation in genetic algorithm to optimize neural network weights and threshold until the output error meets the requirement or it reaches a predetermined number of iterations. Finally, according to the obtained BP neural network weights and threshold, it segments cotton image. The experiment of image segmentation with 136 images photographed in cotton field environment shows that the algorithm can segment cotton image in bright light or shadow accurately and segmentation accuracy rate is up to 91.9% and it converges faster than BP.

Key words: YCbCr space, Genetic Algorithm（GA）, cotton, image segmentation