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An automatic bleeding detection scheme in wireless capsule endoscopy based on histogram of an RGB-indexed image

Wireless capsule endoscopy (WCE) is one of the most effective technologies to diagnose gastrointestinal (GI) diseases, such as bleeding in GI tract. Because of long duration of WCE video containing large number images, it is a burden for clinician to detect diseases in real time. In this paper, an automatic bleeding image detection method is proposed utilizing construction of an index image incorporating certain level of information from each plane of RGB color space. Distinguishable color texture feature is developed from index image by histogram. Support vector machine (SVM) classifier is employed to detect bleeding and non-bleeding images from WCE videos. From extensive experimentation on real time WCE video recordings, it is found that the proposed method can accurately detect bleeding images with high sensitivity and specificity.