Endoscopy process to find the bleeding parts in human body is a complicated work. In ancient mechanism they formally use the wired endoscopy to the patients it will leads to several drawbacks. Thus nowadays wired is changed with wireless capsule endoscopy to overcome the situational hazard of the physician. This is further enhanced by the wireless capsule endoscopy through which it can be used. Wireless Capsule Endoscopy (WCE) is in the form of capsule like format that is used for the further identification by the physician. Here the WCE capture videos of the inner organs. While the physician used to point out the issue, they want to focus on the particular video. There may be manual errors may occur. Thus it can be overcome by the proposed word based color histogram. This model is a promising model to compute the WCE video and predict the accurate result without the burden of the phycisian. It is proposed in this system by including a color features. In this model the RGB color feature is used to predict the bleeding frame. To classify the bleeding Frame two classification algorithms is used. They are Support Vector Machine (SVM) and K Nearest Neighbour (KNN) is proposed in this project. Bleeding frame is identification is maintained and performed with the help of proposed algorithm and techniques are simple and efficient.

WCE, Word based color Histogram, SVM, KNN

[1] D. O. Faigel and D. R. Cave, Capsule endoscopy: Saunders Elsevier, 2008.
[2] M. Yu, "M2a (tm) capsule endoscopy: A breakthrough diagnostic tool for small intestine imaging," Gastroenterology Nursing, vol. 25, pp. 24-27, 2002.
[3] G. Gay, M. Delvaux, and J.-F. Rey, "The role of video capsule endoscopy in the diagnosis of digestive diseases: a review of current possibilities," Endoscopy, vol. 36, pp. 913-920, 2004.
[4] G. Iddan, G. Meron, A. Glukhovsky, and P. Swain, "Wireless capsule endoscopy," Nature, vol. 405, p. 417, 2000.
[5] N. M. Lee and G. M. Eisen, "10 years of capsule endoscopy: an update," 2010.
[6] M. Pennazio, "Capsule endoscopy: Where are we after 6 years of clinical use?," Digestive and Liver Disease, vol. 38, pp. 867-878, 2006.
[7] B. Li and M.-H. Meng, "Computer-aided detection of bleeding regions for capsule endoscopy images," Biomedical Engineering, IEEE Transactions on, vol. 56, pp. 1032-1039, 2009.
[8] R. Francis, "Sensitivity and specificity of the red blood identification (RBIS) in video capsule endoscopy," in The 3rd International Conference on Capsule Endoscopy, 2004.
[9] Y. Fu, W. Zhang, M. Mandal, and M.-H. Meng, "Computer-Aided Bleeding Detection in WCE Video," Biomedical and Health Informatics, IEEE Journal of, vol. 18, pp. 636-642, 2014.
[10] L. Cui, C. Hu, Y. Zou, and M.-H. Meng, "Bleeding detection in wireless capsule endoscopy images by support vector classifier," in Information and Automation (ICIA), 2010 IEEE International Conference on, 2010, pp. 1746-1751.