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Proceedings Paper

Blurry-frame detection and shot segmentation in colonoscopy videos
Author(s): JungHwan Oh; Sae Hwang; Wallapak Tavanapong; Piet C. de Groen; Johnny Wong
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Paper Abstract

Colonoscopy is an important screening procedure for colorectal cancer. During this procedure, the endoscopist visually inspects the colon. Human inspection, however, is not without error. We hypothesize that colonoscopy videos may contain additional valuable information missed by the endoscopist. Video segmentation is the first necessary step for the content-based video analysis and retrieval to provide efficient access to the important images and video segments from a large colonoscopy video database. Based on the unique characteristics of colonoscopy videos, we introduce a new scheme to detect and remove blurry frames, and segment the videos into shots based on the contents. Our experimental results show that the average precision and recall of the proposed scheme are over 90% for the detection of non-blurry images. The proposed method of blurry frame detection and shot segmentation is extensible to the videos captured from other endoscopic procedures such as upper gastrointestinal endoscopy, enteroscopy, cystoscopy, and laparoscopy.

Paper Details

Date Published: 18 December 2003
PDF: 12 pages
Proc. SPIE 5307, Storage and Retrieval Methods and Applications for Multimedia 2004, (18 December 2003); doi: 10.1117/12.527108
Show Author Affiliations
JungHwan Oh, Univ. of Texas/Arlington (United States)
Sae Hwang, Univ. of Texas/Arlington (United States)
Wallapak Tavanapong, Iowa State Univ. (United States)
Piet C. de Groen, Mayo Clinic and Foundation (United States)
Johnny Wong, Iowa State Univ. (United States)

Published in SPIE Proceedings Vol. 5307:
Storage and Retrieval Methods and Applications for Multimedia 2004
Minerva M. Yeung; Rainer W. Lienhart; Chung-Sheng Li, Editor(s)

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