Open AccessIdentification of Mouth Cancer laceration Using Machine Learning Approach
Author(s) -
Prof. Barry Wiling
Publication year - 2018
Publication title -
international journal of new practices in management and engineering
Language(s) - English
Resource type - Journals
ISSN - 2250-0839
DOI - 10.17762/ijnpme.v7i03.66
Subject(s) - artificial intelligence , support vector machine , computer science , pattern recognition (psychology) , histogram equalization , segmentation , adaptive histogram equalization , classifier (uml) , artificial neural network , histogram , machine learning , image (mathematics)
This Paper describes about Identification of Mouth Cancer laceration Using Machine Learning Approach .The SVM algorithm is used for this purpose. Image segmentation operations are performed using: Resizing an image, Gray scale conversion, Histogram equalization and Classifying the Segmented image using SVM. SVM is used to reduce the complexity faced in the existing system comprising of Texture Segmentation and ANN (Artificial Neural Networks) Algorithm. SVM is a simple Machine Learning algorithm when compared to ANN. The outcome of the paper is to segment and classify the Malignancy from the Non-Malignant region using the classifier SVM. SVM performs the classification based on the dataset that contains the trained images.