Title :
Capsule endoscopy video segmentation by spectral clustering
Author :
Baopu Li ; Can Yang ; Wang, Tianfu ; Guoqing Xu ; Qi Zhang ; Meng, Max Q.-H ; Chao Hu
Author_Institution :
Shenzhen Univ., Shenzhen, China
Abstract :
Capsule endoscopy is a new imaging technology for small intestine due to its breakthrough for direct visualization of small intestine for the first time. However, the video data produced for each patient costs a physician much time to inspect. Aiming for reducing the burden of a physician, video scene analysis is indispensable. In this paper, we propose a new video segmentation method to analyze a CE video data since video segmentation is the first step in video scene analysis. A novel color textural feature is utilized to describe the content of the frame in a CE video, then spectral clustering method is applied to segment a CE video into meaningful parts via shot boundary detection. Preliminary experiments on ten short CE videos demonstrate a promising performance of the proposed scheme.
Keywords :
biomedical optical imaging; edge detection; endoscopes; image colour analysis; image segmentation; image texture; medical image processing; pattern clustering; video signal processing; CE video data; capsule endoscopy; color textural feature; imaging technology; shot boundary detection; small intestine; spectral clustering method; video scene analysis; video segmentation; Biomedical imaging; Color; Endoscopes; Image color analysis; Image segmentation; Medical services; Wireless communication; CE video; segmentation; spectral clustering; textural feature;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
DOI :
10.1109/WCICA.2014.7052848