Affiliations: [a] Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn, Malaysia
| [b]
Department of Electronics and Communication Engineering, KPR Institute of Engineering and Technology, Coimbatore, India
| [c]
Department of ECE, Karunya Institute of Technology and Sciences, Coimbatore, India
| [d]
Department of Signal Theory and Communications and Telematics Engineering, University of Valladolid, Spain
Correspondence:
[*]
Corresponding author. Dr. Ashok Vajravelu, Faculty of Electrical and Electronic Engineering, UniversitiTun Hussein Onn, Malaysia. E-mail: ashokvajravelu8@gmail.com.
Abstract: Wireless Capsule Endoscopy (WCE) allows direct visual inspecting of the full digestive system of the patient without invasion and pain, at the price of a long examination by physicians of a large number of photographs. This research presents a new approach to color extraction to differentiate bleeding frames from normal ones and locate more bleeding areas. We have a dual-system suggestion. We use entire color information on the WCE pictures and the pixel-represented clustering approach to get the clustered centers that characterize WCE pictures as words. Then we evaluate the status of a WCE framework using the nearby SVM and K methods (KNN). The classification performance is 95.75% accurate for the AUC 0.9771% and validates the exciting performance for bleeding classification provided by the suggested approach. Second, we present a two-step approach for extracting saliency maps to emphasize bleeding locations with a distinct color channel mixer to build a first-stage salience map. The second stage salience map was taken with optical contrast.We locate bleeding spots following a suitable fusion approach and threshold. Quantitative and qualitative studies demonstrate that our approaches can correctly distinguish bleeding sites from neighborhoods.
Keywords: Bleeding classification and region detection, words-based color histograms, wireless capsule endoscopy
