Open AccessAutomatic Liver Cancer Detection using Sobel Edge Detection & Morphological Dilation in Digital Image Processing
Author(s) -
Vijay Laxmi Yadav,
Anubhuti Khare
Publication year - 2020
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.l8011.1091220
Subject(s) - sobel operator , computer science , liver cancer , artificial intelligence , word error rate , edge detection , computer vision , dilation (metric space) , image processing , constant false alarm rate , task (project management) , enhanced data rates for gsm evolution , alarm , pattern recognition (psychology) , cancer , image (mathematics) , medicine , mathematics , management , combinatorics , economics , materials science , composite material
Image processing is a field that is widely used in medical science to identify various cancers or tumors. Diagnosing liver cancer is not an easy task and is usually performed by doctors and diagnosed manually. Filtering technique should be used precisely by not compromising the sensitive information. Most of the technique may distort the actual information that causes false alarm rate. A liver is an uneven or bit complex in structure where there are various spots may be considered as tumor that provokes the system towards invalid turing test. This paper proposes a system that would be able to recognize cancer automatically from a tomographical image along with high precision that stabilize the system with less processing time. Here the objective of the system is to obtain the result using Sobel operator that retains edges and eroding the unwanted areas and preceding high accuracy with less error rate. System also intended to extract the impaired area that has been affected by liver cancer. System acquired the better precision rate as compare to the previously implemented systems with minimal error rate.