ISSN : 1796-2048
Volume : 1    Issue : 1    Date : April 2006

Automatic Detection of Targets Using Center-Surround Difference and Local Thresholding
Sun-Gu Sun and Dong-Min Kwak
Page(s): 16-23
Full Text:
PDF (1,760 KB)

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.

Index Terms
binary template matching, center-surround difference, forward looking infrared, local thresholding,
target detection