
Research on SVM and KNN Classifiers for Skin Cancer Detection
Author(s) -
A. Murugan,
Dinesh Nair,
Dhirendra Kumar
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.b5117.129219
Subject(s) - support vector machine , artificial intelligence , pattern recognition (psychology) , segmentation , laptop , computer science , classifier (uml) , feature extraction , k nearest neighbors algorithm , operating system
Generally, a not unusual skin ailment in human disorder. In laptop imaginative and prescient applications, coloration is a sturdy indication for this sickness. This machine identifies pores and skin cancer based totally on the picture of the pores and skin. Initially, the skin image is filtered using filters and segmented Gausian the use of energetic contour segmentation. Segmented pix are fed as an input to the feature extraction. Pictures extracted classified the use of class strategies such as Support Vector Machine classifiers(SVM) and k Nearest Neighbor(kNN) classifiers. SVM classifier provided better results than kNN classifier