Tank segmentation of infrared images with complex background for the homing anti-tank missile

In an effort to achieve fast and effective tank segmentation of infrared images under complex background for the homing anti-tank missile, the threshold of the maximum between-class variance method (i.e., the Otsu method) is experimentally analyzed, and the working mechanism of the Otsu method is revealed. Subsequently, a fast and effective method for tank segmentation under complex background is proposed based on the Otsu method by constraining the image background pixels and gray levels. Firstly, with the prior information of the tank, derive the equation to calculate the number of pixels of tank according to optical imaging principle, and then use the calculated tank size to constrain the image background pixels. Secondly, employ the golden section to restrict the background gray levels. Finally, use the Otsu method to implement the segmentation of the tank. Experimental results demonstrate that the proposed method can get as an ideal result as the manual segmentation with less running time. (C) 2016 Elsevier B.V. All rights reserved.