Segmentation Algorithm Study for Infrared Images with Occluded Target Based on Artificial Immune System
Image segmentation is an important component of image processing.The improvements of the segmentation efficiency and quality are the two significant issues for each segmentation algorithm.This paper proposed a segmentation algorithm based on the negative selection mechanism of the artificial immune system.The algorithm can extract the occluded target in an infrared image by using a template constructed from negative selection method.A segmentation algorithm combined with the information entropy and the clonal selection algorithm is introduced to avoid the drawbacks of dcciding a segmentation threshold subjectively.The simulation results presented that the two proposed algorithms do have some advantages on the segmentation of the occluded target in an infrared image,especially the latter can acquire a stable result leading to an ideal effect.
negative slection clonal selection entropy image segmentation
Ting-ting Wang Dong-mei Fu Peng Chen
College of information Engineering,University of Science and Technology Beijing Beijing,China
国际会议
太原
英文
473-476
2011-02-26（万方平台首次上网日期，不代表论文的发表时间）