Automatic Detection of Targets Using Center-Surround Difference and Local Thresholding

This paper proposes a new target detection method in low contrast forward looking infrared (FLIR) images. Automatic detection of small targets in remotely sensed images is a difficult and challenging work. The goal is to find out target locations with low false alarms in a thermal infrared scene of battlefield. The interesting targets are military vehicles such as battle tanks and armored personal carriers in ground-to-ground scenarios. The proposed method consists of three following stages. First, center-surround difference is proposed in order to find salient areas in an input image. Second, local thresholding for a region of interest (ROI) is proposed. The ROI is selected on the basis of a salient region that is the result of first step. Third, the shape of extracted binary images is compared with binary target templates using size and affinity to remove clutters. In the experiments, the proposed method is compared with morphology method using many natural infrared images with high variability. The result demonstrates that our method is superior to the morphological method in terms of receiver operating characteristic (ROC) curve and average computation time.