Publication in refereed journal
香港中文大学研究人员 ( 现职)
| 孟庆虎教授 (电子工程学系) |
| 李抱朴博士 (电子工程学系) |
全文
| 数位物件识别号 (DOI) ○○@http://aims.cuhk.edu.hk/converis/portal/Publication/3$@○○ |
引用次数
Web of Sciencehttp://aims.cuhk.edu.hk/converis/portal/Publication/3WOS source URL
其它资讯
摘要Wireless capsule endoscopy (WCE) needs computerized method to reduce the review time for its large image data. In this paper, we propose an improved bag of feature (BoF) method to assist classification of polyps in WCE images. Instead of utilizing a single scale-invariant feature transform (SIFT) feature in the traditional BoF method, we extract different textural features from the neighborhoods of the key points and integrate them together as synthetic descriptors to carry out classification tasks. Specifically, we study influence of the number of visual words, the patch size and different classification methods in terms of classification performance. Comprehensive experimental results reveal that the best classification performance is obtained with the integrated feature strategy using the SIFT and the complete local binary pattern (CLBP) feature, the visual words with a length of 120, the patch size of 8*8, and the support vector machine (SVM). The achieved classification accuracy reaches 9http://aims.cuhk.edu.hk/converis/portal/Publication/3.2%, confirming that the proposed scheme is promising for classification of polyps in WCE images.
着者Yuan YX, Li BP, Meng MQH
期刊名称IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
出版年份2016
月份4
日期1
卷号1http://aims.cuhk.edu.hk/converis/portal/Publication/3
期次2
出版社IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
页次529 - 5http://aims.cuhk.edu.hk/converis/portal/Publication/35
国际标準期刊号1545-5955
电子国际标準期刊号1558-http://aims.cuhk.edu.hk/converis/portal/Publication/378http://aims.cuhk.edu.hk/converis/portal/Publication/3
语言英式英语
关键词Improved bag of feature method; integration of features; polyp detection; wireless capsule endoscopy images
Web of Science 学科类别Automation & Control Systems
