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Target Detection Using Texture Features and Neural Network in Infrared Images  

Sun, Sun-Gu (Agency for Defense Development)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SC / v.47, no.5, 2010 , pp. 62-68 More about this Journal
Abstract
This study is to identify target locations with low false alarms on thermal infrared images obtained from natural environment. The proposed method is different from the previous researches because it uses morphology filters for Gabor response images instead of an intensity image in initial detection stage. This method does not need precise extracting a target silhouette to distinguish true targets or clutters. It comprises three distinct stages. First, morphological operations and adaptive thresholding are applied to the summation image of four Gabor responses of an input image to find out salient regions. The locations of extracted regions can be classified into targets or clutters. Second, local texture features are computed from salient regions of an input image. Finally, the local texture features are compared with the training data to distinguish between true targets and clutters. The multi-layer perceptron having three layers is used as a classifier. The performance of the proposed method is proved by using natural infrared images. Therefore it can be applied to real automatic target detection systems.
Keywords
Automatic target detection; forward-looking infrared; Gabor response; morphology; multi-layer perceptron;
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Times Cited By KSCI : 1  (Citation Analysis)
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