NDLI: SAR Image Target Recognition Based on Hu Invariant Moments and SVM

Content Provider	IEEE Xplore Digital Library
Author	Fu Yan Wang Mei Zhang Chunqin
Copyright Year	2009
Abstract	Target recognition is a key step in the application of SAR images, but because of the existing of speckles in SAR images, targets can not be recognized well by using traditional methods. According to the advantages of invariant moments extraction and support vector machine (SVM) classification, an efficient method of SAR image target recognition is proposed. First, image preprocessing is performed by using wavelet transform. Second, seven Hu moments, which have the properties of rotation invariability, translation invariability and scaling invariability, are extracted as feature vectors and are normalized. Then a SVM classifier is designed and trained by using normalized feature vectors. Finally, the testing sets of SAR images are recognized by trained SVM. In the experiments of recognizing planes and tanks, better results have been obtained with this new method.
Starting Page	585
Ending Page	588
File Size	211389
Page Count	4
File Format	PDF
ISBN	9780769537443
DOI	10.1109/IAS.2009.289
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Target recognition Support vector machines Support vector machine classification Image recognition Feature extraction Data mining Testing Machine learning Synthetic aperture radar Information security Support Vector Machine SAR image target recognition invariant moments
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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