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This paper proposes an image segmentation method for blurred trace infrared images, exploring statistical properties of blurred infrared data to segment target regions. I consider the function of immune factors for blurred infrared image segmentation, combined to the template algorithm framework. First, all of the pixel antigens are divided into three classes by innate recognition factors: target antigens, background antigens and blurred antigens. Next, the innate presentation factors present template characteristics as new features for each antigen. Finally, target and background antigens are used for generating mature adaptive immune factors, and these mature factors will recognise each blurred antigen into two classes: a target pixel or a background pixel. Experimental results indicate that the superstring galaxy template algorithm can improve the target segmentation rate and reduce the segmentation error rate. [ABSTRACT FROM AUTHOR]