%0 Journal Article
	%A R. Xu and  X. Zhao and  X. Li and  C. Kwan and  C.-I Chang
	%D 2008
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 15, 2008
	%T Target Detection with Improved Image Texture Feature Coding Method and Support Vector Machine
	%U https://publications.waset.org/pdf/6253
	%V 15
	%X An image texture analysis and target recognition approach of using an improved image texture feature coding method (TFCM) and Support Vector Machine (SVM) for target detection is presented. With our proposed target detection framework, targets of interest can be detected accurately. Cascade-Sliding-Window technique was also developed for automated target localization. Application to mammogram showed that over 88% of normal mammograms and 80% of abnormal mammograms can be correctly identified. The approach was also successfully applied to Synthetic Aperture Radar (SAR) and Ground Penetrating Radar (GPR) images for target detection.

	%P 966 - 975