Title :
Medical Image Segmentation Based on Genetic Algorithm
Author :
Guan Xiao-wei ; Zhu Xia ; Gao Shangbing
Author_Institution :
JiangSu Vocational & Tech. Coll. of Finance & Econ., Huai´an, China
Abstract :
As one of the difficulties and hot of computer vision and image processing. Image segmentation is highly valued by the research workers. In this paper, Genetic Algorithm (GA) has proposed to segment the image. With global searching capacity and the largest variance between clusters as the fitness function, this method can search the optimal threshold of edge detection automatically, and extract the edge of image by combining morphologic processing to realize the segmentation. Experiment shows that the method can not only simplify the segmentation, but also achieve a good segmentation effect and can improve the efficiency and quality of the picture to some extent. The results show that GA algorithm is very stable, and the fusion result is more satisfactory. Thus, GA can be applied in image segmentation and it has a good foreground in application in image processing.
Keywords :
edge detection; genetic algorithms; image segmentation; medical image processing; computer vision; edge detection; fitness function; genetic algorithm; global searching capacity; image processing; medical image segmentation; Algorithm design and analysis; Computers; Conferences; Genetic algorithms; Image edge detection; Image segmentation; genetic algorithm (GA); image segmentation; thresholding;
Conference_Titel :
Information Technology, Computer Engineering and Management Sciences (ICM), 2011 International Conference on
Conference_Location :
Nanjing, Jiangsu
Print_ISBN :
978-1-4577-1419-1
DOI :
10.1109/ICM.2011.97