TUMOR RECOGNITION IN WIRELESS CAPSULE ENDOSCOPY IMAGES USING TEXTURAL FEATURES AND SVM-BASED FEATURE SELECTION
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ABSTRACT:
Tumor in digestive tract is a common disease and wireless capsule endoscopy (WCE) is a
relatively new technology to examine diseases for digestive tract especially for small intestine.
This paper addresses the problem of automatic recognition of tumor for WCE images.
Candidate color texture feature that integrates uniform local binary pattern and wavelet is
proposed to characterize WCE images. The proposed features are invariant to illumination
change and describe multiresolution characteristics of WCE images.
Tissue feature selection classify by SVM based RFE and Naive Bayes Classifier
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