Target Detection with Improved Image Texture Feature Coding Method and Support Vector Machine

نویسندگان

  • R. Xu
  • X. Zhao
  • X. Li
  • C. Kwan
  • C. - I Chang
چکیده

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. Keywords—Image texture analysis, Feature extraction, Target detection, Pattern classification

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Abstract—An image texture analysis and target recognition approach of using an improved image texture feature coding method (TFCM) and Support Vector Machine

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 s...

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تاریخ انتشار 2012