Target extraction of blurred infrared image with an immune network template algorithm

•A coordination immune network template algorithm for extracting target from blurred infrared image is proposed.•The topology of the algorithm reflects the coordination mechanism between innate immunity and adaptive immunity.•The designing process of immune network template reflects the space-domain and the frequency-domain characteristics of the blurred infrared image.

To extract targets from blurred infrared images efficiently, this paper presents a coordinated immune network template algorithm based on the coordination mechanism between innate immunity and adaptive immunity. First, the neighbourhood characteristics for every pixel in a blurred infrared image are computed as the template features of each pixel. Next, all of the pixels are divided into three sets according to their grey level values: a target set, a background set and a blurred set. Finally, the pixels in the target set and the background set are used for training the adaptive network, which can divide each blurred pixel into two classes: a target pixel or a background pixel. Experimental results on the hand trace infrared images verified that the proposed algorithm could efficiently extract targets from images and produce better extraction accuracy.