A Target Extraction Method of Infrared Image Based on Edge and Transition Region

Traditional target segmentation based on transition region is sensitive to noise, which can affect the accuracy of the extraction. Compared with the visible image, the thermal noise caused by the detector in infrared image would degrade the detection rate of traditional target extraction method. In addition, although the target can be accurately positioned through the edge, it is impossible to obtain the complete edge of the target. However, the gray distribution of the transition region can solve the problem of edge. Therefore, in order to improve its anti-noise and target extraction performance, an adaptive target extraction method of infrared image utilizing edge and transition region is proposed. First of all, the pixel's density with inform of spatial neighbors is calculated to reduce noise and obtain edges. After that, the separation between object and background is made to get transition region with edge, which is utilized to grow up the whole object. Finally, performance of anti-noise is estimated by extracting objects in several complex infrared scenes. The results show that the proposed algorithm is effective under man-added noise conditions.