Floating pollutant image target extraction algorithm based on immune extremum region

With the continuous development of human society, people's over-exploitation of nature leads to frequent environmental problems. A large number of floating objects appear on lakes, rivers, reservoirs and other water surfaces. Water floats have seriously damaged the ecological environment and directly threatened the survival and development of human beings. Therefore, for the sustainable development of human beings, we must solve the problem of water pollution. The detection of floating pollutants on water surface is the primary goal of water resource management. It is difficult to distinguish and identify water surface and pollutants when distortion and deformation occur due to illumination and other environmental factors. In this paper, based on the image of environmental water surface pollutants and the theory of region feature extraction based on artificial immune algorithm, a method of sewage floating object extraction based on immune extreme region is proposed to realize the recognition and detection of water surface pollutants. Algorithm of water pollutants through multi-scale Gaussian function image illumination correction, the congenital immune mechanism is adopted to the surface of the water pollutants at the beginning of the image segmentation, reduce the effects of other environmental factors, and then based on adaptive immunity immune extremum region affine invariability, recognition and detection figure floating pollutant distribution. Simulation results show that the proposed method is feasible. Compared with other traditional algorithms, the proposed method can effectively detect, identify and divide floating pollutants on water surface, which provides certain help for water resources management and protection.