removal of non-informative frames for wireless capsule endoscopy video segmentation

ISCAS OpenIR

	removal of non-informative frames for wireless capsule endoscopy video segmentation
	Sun Zhe; Li Baopu; Zhou Ran; Zheng Huimin; Meng Max Q.-H
	2012
会议名称	2012 IEEE International Conference on Automation and Logistics, ICAL 2012
会议录名称	IEEE International Conference on Automation and Logistics, ICAL
页码	294-299
会议日期	August 15, 2012 - August 17, 2012
会议地点	Zhengzhou, China
收录类别	EI
ISSN	2161-8151
ISBN	9781467303620
部门归属	(1) School of Software Engineering University of Science and Technology of China Hefei China; (2) Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China; (3) Department of Electronic Engineering Chinese University of Hong Kong Hong Kong Hong Kong
摘要	Wireless capsule endoscopy (WCE) video segmentation plays an important part in WCE automatic diagnosis since it provides an effective method to help physicians and save time. In the automatic WCE video segmentation process, impurities frames with opaque digestive juice, food residues and excrement not only waste plentiful time, but also cause a lower accuracy of segmentation for its variation of color and pattern. The major impurities which have great affection for WCE video segmentation can be divided into two categories, gastric juice and bubbles. Thus, in this paper, a novel two-stage preprocessing approach is proposed to remove impurities frames in WCE videos. In the first stage, frames of gastric juice are eliminated by using local HS histogram features. In the second stage, a new approach is carried out to remove the bubbles frames in the WCE video, which combines Color Local Binary Patterns (CLBP) algorithm with Discrete Cosine Transform (DCT). K-Nearest Neighbor (KNN) classifier is used in both stages for its rapidity. Experiments demonstrate that the proposed scheme is an effective approach for removing non-informative frames in WCE video and the accuracies of each stage can reach as high as 99.31% and 97.54% respectively. © 2012 IEEE.; Wireless capsule endoscopy (WCE) video segmentation plays an important part in WCE automatic diagnosis since it provides an effective method to help physicians and save time. In the automatic WCE video segmentation process, impurities frames with opaque digestive juice, food residues and excrement not only waste plentiful time, but also cause a lower accuracy of segmentation for its variation of color and pattern. The major impurities which have great affection for WCE video segmentation can be divided into two categories, gastric juice and bubbles. Thus, in this paper, a novel two-stage preprocessing approach is proposed to remove impurities frames in WCE videos. In the first stage, frames of gastric juice are eliminated by using local HS histogram features. In the second stage, a new approach is carried out to remove the bubbles frames in the WCE video, which combines Color Local Binary Patterns (CLBP) algorithm with Discrete Cosine Transform (DCT). K-Nearest Neighbor (KNN) classifier is used in both stages for its rapidity. Experiments demonstrate that the proposed scheme is an effective approach for removing non-informative frames in WCE video and the accuracies of each stage can reach as high as 99.31% and 97.54% respectively. © 2012 IEEE.
关键词	Body Fluids Discrete Cosine Transforms Endoscopy Removal
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/15841
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Sun Zhe,Li Baopu,Zhou Ran,et al. removal of non-informative frames for wireless capsule endoscopy video segmentation[C],2012:294-299.