Extracting targets from a blurred midwave infrared image is a challenging task due to the fuzziness of the image. Inspired by the coordination mechanism between biological innate immunity and adaptive immunity, an immune template clustering targets extraction method is proposed, which based on imaging mechanism and template statistical property of midwave image. Firstly, by learning from the recognition function of innate immunity and maximizing the between-cluster variance, a midwave blurred infrared image is segmented into a target pixel set, a background pixel set and a blurred pixel set. Secondly, according to the presentation function of innate immunity, the frequency domain template features of pixels in midwave blurred infrared image are extracted. Finally, adaptive immune clustering is completed for the blurred pixel set based on frequency domain template feature, in order to divide each blurred pixel into target pixel or background pixel. Experimental results show that the proposed algorithm can extract targets from a midwave blurred infrared image efficiently. Compared with classical edge template and conventional region template methods, the immune template clustering method has better extraction efficiency, absolute error rate and coincidence degree with ground truth.