Computer-aided diagnosis system for ulcer detection in wireless capsule endoscopy videos

In this paper, we present a new feature descriptor for automatic recognition of frames with ulcer in Wireless Capsule Endoscopy (WCE) images. The new approach is based on the fact that the ulcer disease exhibits various features that can not be detected with a single descriptor. Hence, we have combined two stages of the art descriptors in order to get more powerful one. Complete Local Binary Pattern (CLBP) descriptor is used to detect the texture information in the image. In parallel, the Global Local Oriented Edge Magnitude Pattern (Global LOEMP) descriptor is employed to extract the color features. Finally, we combine the feature vectors to get a more discriminating one. Experiments were conducted and the results are satisfactory.