
Advanced Region Detection Technique to Enhance Accurate Abnormality Isolation of Cancer in Digital Images
Author(s) -
N. M. Mallika,
Srinivasan Janarthanam,
A. Aruljoth
Publication year - 2019
Publication title -
asian journal of computer science and technology
Language(s) - English
Resource type - Journals
eISSN - 2583-7907
pISSN - 2249-0701
DOI - 10.51983/ajcst-2019.8.s1.1973
Subject(s) - thresholding , segmentation , artificial intelligence , computer science , pattern recognition (psychology) , contrast (vision) , cancer detection , image segmentation , image processing , feature extraction , feature (linguistics) , computer vision , image (mathematics) , cancer , medicine , linguistics , philosophy
In recent years, extensive research is carried out in computer assisted interpretation carried out for cancer classification. Computer aided Interpretations are involves with pre-processing, contrast enhancement, segmentation, appropriate feature extraction and classification. Though considerable research is carried out in developing contrast enhancement and image segmentation techniques, cancer regions could not be isolated and extracted efficiently. Hence this work focuses on developing efficient image segmentation techniques for isolating the cancer region and also identifying suitable descriptors for describing the cancer region. Hence this work focuses to introduce a simple and easy approach for detection of cancerous tissues in mammals. Detection phase is followed by segmentation of the region in an image. Our approach uses simple image processing techniques such as averaging and thresholding along with a Max-Mean and Least-Variance technique for cancer detection. Experimental results demonstrate the effectiveness of our approach.