Wireless Capsule Endoscopy Video Reduction Based on Camera Motion Estimation

Abstract

Wireless capsule endoscopy (WCE) is a novel technology aiming for investigating the diseases and abnormalities in small intestine. The major drawback of WCE examination is that it takes a long time to examine the whole WCE video. In this paper, we present a new reduction scheme for WCE video to reduce the examination time. To achieve this task, a WCE video motion model is proposed. Under this motion model, the WCE imaging motion is estimated in two stages (the coarse level and the fine level). In the coarse level, the WCE camera motion is estimated with a combination of Bee Algorithm and Mutual Information. In the fine level, the local gastrointestinal tract motion is estimated with SIFT flow. Based on the result of WCE imaging motion estimation, the reduction scheme preserves key images in WCE video with scene changes. From experimental results, we notice that the proposed motion model is suitable for the motion estimation in successive WCE images. Through the comparison with APRS and FCM-NMF scheme, our scheme can produce an acceptable reduction sequence for browsing and examination.