Automatic Classifier for Skin Disease Using k-NN and SVM

被引：7
|
作者：
Nosseir, Ann [1 ,2 ]
Shawky, Mokhtar Ahmed [3 ]
机构：
[1] INP, Cairo, Egypt
[2] British Univ Egypt, BUE ICS Dept, Cairo, Egypt
[3] BUE ICS Dept, Cairo, Egypt
来源：
PROCEEDINGS OF 2019 8TH INTERNATIONAL CONFERENCE ON SOFTWARE AND INFORMATION ENGINEERING (ICSIE 2019) | 2019年
关键词：
Image recognition; k-NN classifier; Multi SVM;
D O I：
10.1145/3328833.3328862
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
Accurate diagnose of skin diseases from images is good for early treatment. This work develops a novel algorithm to differentiate between Warts, Hemangiomas and Vitiligo skin diseases. The algorithm is based on both skin color and texture features (features derives from the GLCM) to give a better and more efficient recognition accuracy of skin diseases. The work compares between accuracy of two supervised classifiers namely, k-nearest neighbor algorithm (k-NN) and Multi Support vector machine (SVM). The results of the K-NN is better 98.2%.
引用
收藏
页码：259 / 262
页数：4
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