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Optical Engineering

Segmentation of forward-looking infrared image using fuzzy thresholding and edge detection
Author(s): SunGu Sun; Hyun Wook Park
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Paper 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 FLIR 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 FLIR 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.

Paper Details

Date Published: 1 November 2001
PDF: 8 pages
Opt. Eng. 40(11) doi: 10.1117/1.1409563
Published in: Optical Engineering Volume 40, Issue 11
Show Author Affiliations
SunGu Sun, Korea Advanced Institute of Science and Technology (South Korea)
Hyun Wook Park, Korea Advanced Institute of Science and Technology (South Korea)


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