Automatic bleeding detection in wireless capsule endoscopy based on RGB pixel intensity ratio

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 the variation of pixel intensities in RGB color planes. Based on statistical behavior of bleeding and non-bleeding pixel intensities in terms of pixel intensity ratio in different planes, distinguishing color texture feature of an image is developed. 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.