Novel training and comparison method for blood detection in wireless capsule endoscopy images

Abstract

Wireless capsule endoscopy (WCE) is a device used to inspect the gastrointestinal (GI) track. This technology is noninvasive compared to other methods that are traditionally adopted in the examination of GI track. From the physicians' point of view, the WCE is a favorable approach because of its efficiency and accuracy. In this paper, a new discriminant mechanism of bleeding regions is proposed based on the use of Support Vector Machine (SVM) classifier. Different from the traditional SVM approach, in the proposed method single pixels are not used for training and testing data, however a cluster of pixels are used. This approach aims to eliminate some very small judged bleeding areas which in fact are not. The reported results demonstrate that the accuracy of the proposed method is significantly increased in comparison with traditional approaches. In addition, another improved method based on the square comparison is also proposed, and this has increased the gain.