Open AccessSFTA and GLCM via LDA Classifier for Skin Cancer Detection
Author(s) -
Mohd Nasir Omar,
Muhammad Naufal Mansor,
Syahrul Affandi Saidi
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/932/1/012068
Subject(s) - artificial intelligence , classifier (uml) , pattern recognition (psychology) , gabor filter , feature extraction , computer science , computer vision
Skin cancer may be a serious tumor. This can be clearly seen through the mature, uncommon appearance of fur pathology, which has abnormal properties in complex situations, wrinkled or uncertain perimeters, and dual colors. A small number of tulle melanomas of uncertain diameter can imitate benign moles and cannot be perceived by optical inspection. The only assumption for analyzing them is through dermoscopy as an option. Original identification and medical surgery can alternative for the patients. Within this research a detection method through image processing with various feature extraction such as Gabor filter and Hu Moment were employed and substantially improves the diagnosis performance with 97% via LDA Classifier.