IR target detection based on improved K-means clustering

Considering the variance of image was a very good response for edge information, a target detection algorithm by K-means clustering algorithm based on variance was presented. First, this paper prepressed the infrared image by morphological method, and calculated the corresponding variance image by using a specific template, then gathered each difference image class by using the K-means clustering method, finally the different target edge information was got. Experimental results show that the algorithm can effectively extract the IR target edge.