Loading

Endoscopic Video Pre-Processing using Histogram Equalization and Canny Edge Detection Technique and Hough Transform Technique for Polyp Detection
Nagesh B S1, N P Kavya2
1Nagesh B S, Research Scholar, Dept. of CSE, R N S Institute of Technology, Bengaluru, India.
2Dr. N P Kavya, Professor, Department of CSE R N S Institute of Technology, Bengaluru, India.

Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 1793-1795 | Volume-8 Issue-4, November 2019. | Retrieval Number: C6133098319/2019©BEIESP | DOI: 10.35940/ijrte.B6133.118419

Open Access | Ethics and Policies | Cite  | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Paper An effective image processing approach has been shown to process real time endoscopic videos to support practitioners in taking vital decisions regarding cancer patients. The images are extracted from real time endoscopy videos using the available software and fed into Matlab for image processing, the results of the processed videos are returned back to the host software. Image processing techniques are used to recognize and enhance the visualization of the polyps present in gastro intestinal tract which help the practitioners in decision making. The intention of the system is to assist the physician or medical practitioner for better visualization and identifying abnormal structures like polyps and bleeding regions during the endoscopic procedures. This proposed system is experimented on the recorded gastrointestinal dataset which contains ten sequence videos with 7894 total frames.
Keywords: Endoscopy, Video Mining, Image Processing.
Scope of the Article: Signal and Image Processing.