TY  - CONF
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030756852&doi=10.1145%2f3095713.3095731&partnerID=40&md5=2c3231a30767ccaa894450a682df0adc
A1  - Suman, S.
A1  - Hussin, F.A.B.
A1  - Malik, A.S.
A1  - Pogorelov, K.
A1  - Riegler, M.
A1  - Ho, S.H.
A1  - Hilmi, I.
A1  - Goh, K.L.
VL  - Part F
Y1  - 2017///
SN  - 9781450353335
PB  - Association for Computing Machinery
N1  - cited By 16; Conference of 15th International Workshop on Content-Based Multimedia Indexing, CBMI 2017 ; Conference Date: 19 June 2017 Through 21 June 2017; Conference Code:130150
N2  - Wireless capsule endoscopy (WCE) is a modern and efficient technology to diagnose complete gastrointestinal tract (GIT) for various abnormalities. Due to long recording time of WCE, it acquires a huge amount of images, which is very tedious for clinical expertise to inspect each and every frame of a complete video footage. In this paper, an automated color feature based technique of bleeding detection is proposed. In case of bleeding, color is a very important feature for an efficient information extraction. Our algorithm is based on statistical color feature analysis and we use support vector machine (SVM) to classify WCE video frames into bleeding and non-bleeding classes with a high processing speed. An experimental evaluation shows that our method has promising bleeding detection performance with sensitivity and specificity higher than existing approaches. © 2017 Copyright is held by the owner/author(s).
KW  - Color; Endoscopy; Image classification; Indexing (of information); Support vector machines
KW  -  Bleeding detections; Color features; Efficient technology; Experimental evaluation; Gastrointestinal tract; Important features; Sensitivity and specificity; Wireless capsule endoscopy
KW  -  Feature extraction
ID  - scholars8597
TI  - Detection and classification of bleeding region in WCE images using color feature
AV  - none
ER  -