Infrared target detection based on shape characteristics

For the infrared image of fixed target without available base image,it is difficult to recognize the target due to the blurry target edge.A new target detection algorithm based on shape characteristics matching is proposed.Firstly,based on shape characteristics of infrared image,the mathematic morphological gradient algorithm is introduced in order to expand contrast and strengthen edge character.Secondly,multi seed-regions are designed,and similarity calculation of pixels is introduced.Pixels′ gray information and spatial location are integrated efficiently.Lastly,considering the impact of unreal edge,Canny operator is added into the edge detection for separating the target and background.The requisite target is detected in the real infrared image.Experiment results show that the detection probability can reach up to 80%.Comparing to histogram detection algorithm,Hausdorff distance algorithm and Nprod algorithm,the probability increases by 10%,11% and 12% respectively and the spent time is shortened to 2/3.This method has better performance at detection probability,computing speed and recognition precision.