Research Of Infra-red Image Segmentation Based On Genetic Algorithm

Infra-red Technology plays a crucial role in military and civilian fields in the 21st Century, and with the needs in the future battlefield and the continuous development of the national economy, infra-red technology will become more and more important. Infra-red target recognition technology is one of the forefront and hot issues researched by academic researchers around the world. The content of this paper is a part of the subject, infrared target recognition technology, mainly involving infra-red image segmentation.Genetic algorithm is a random search optimization method, which is based on biological and genetic mechanism of natural selection. It has the outstanding advantages of simpleness, robustness and good nature of parallel and adaptive. In a variety of applications, it has made great success, and aroused the attention of scholars; genetic mechanism is introduced into the field of image segmentation, which can effectively solve image segmentation problem, the high computational complexity, computing a long time, etc. This paper will discuss the genetic algorithm, image segmentation and other related theories. It has analyzed the infra-red image characteristics, introduced several image segmentation algorithms, and introduces an optimized algorithm genetic, hierarchical genetic algorithm into the two dimensional entropy image segmentation operator. On the pr emise of without reducing the image segmentation quality, it optimizes the searching process, improves the speed, and the results show that the algorithm of infra-red image segmentation is effective.