Segmentation of forward-looking infrared image using fuzzy thresholding and edge detection

Abstract

A new segmentation algorithm is proposed to extract a target in forward-looking IR (FLIR) images. It is based on fuzzy thresholding and edge detection. First, a region of interest (ROI) selection method is applied to the FUR image to remove complex background and to automatically extract a small rectangular ROI including a target. Then fuzzy thresholding, which uses intensity and spatial information, is performed on the ROI. The Canny edge method is utilized to supplement the deficiency of the threshold method. As a preprocessing of edge detection, a new contrast extension method using a gray level mathematical morphology operation is proposed to sharpen edges. The proposed segmentation algorithm is applied to many natural FUR images and its performance is compared with conventional segmentation methods. Experimental results show that the proposed algorithm is fast and has a good segmentation performance. (C) 2001 Society of Photo-Optical Instrumentation Engineers.