The infrared ship segmentation in digital images is a fundamental step in the process of ship recognition. This paper presents an adaptive recursive algorithm for infrared ship image segmentation based on the gray-level histogram analysis of the image. The proposed algorithm consists of four phases. First, the gray-level histogram of the image is generated and de-noised by using wavelets transform. Second, a threshold level which best extracts the ship from the water region is selected according to the histogram profile analysis. Third, the rationality of the selected threshold is analyzed based on the prior information about infrared ship images. If the selected threshold is not reasonable, we can still use it as the recursive initial threshold and the infrared ship image will be further segmented with a local recursive method based on the method proposed by OTSU until it reaches the prescriptive termination criteria. Finally, we eliminate the spurious pixels by extracting the greatest connected region and filling the holes. The segmentation algorithm works successfully for classification of infrared ships, and some experimental results are also presented.