Ulcer detection in wireless capsule endoscopy images

Lecheng Yu*, Pong Chi YUEN, Jianhuang Lai

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

35 Citations (Scopus)

Abstract

The invention of wireless capsule endoscopy greatly helps physician to view small intestine images without causing much pain to patients. It becomes very popular around the world for its usability and performance. However, physician requires a long time (around 45 minutes) to examine a capsule endoscopy video generated from each examination. In this paper, we propose a new image processing method using combination of local features for ulcer detection. The proposed method is developed based on bag-of-words model and feature fusion technique. Image patches are described by LBP and SIFT features. The pyramid bag-of-words is employed to model and represent the images, and SVM classifiers are trained. Finally feature fusion technique is employed to draw a final conclusion. Experimental results show that the proposed method outperforms single feature methods and existing methods.

Original languageEnglish
Title of host publicationProceedings of the 21st International Conference on Pattern Recognition (ICPR2012)
PublisherIEEE
Pages45-48
Number of pages4
ISBN (Print)9784990644109
Publication statusPublished - Nov 2012
Event21st International Conference on Pattern Recognition, ICPR 2012 - Tsukuba, Japan
Duration: 11 Nov 201215 Nov 2012

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Conference

Conference21st International Conference on Pattern Recognition, ICPR 2012
Country/TerritoryJapan
CityTsukuba
Period11/11/1215/11/12

Scopus Subject Areas

  • Computer Vision and Pattern Recognition

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