Scopus Indexed Publications

Paper Details


Title
Skin Disease Recognition: A Machine Vision Based Approach
Author
Anika Nawar, Al Amin Biswas, Masud Rabbani, Noor Kibria Sabuz, Shah Md. Tanvir Siddiquee,
Email
anika.cse0303.c@diu.edu.bd
Abstract
Progressively a large number of people are being invaded by various types of skin diseases all over the world. With the help of modern medical equipment, it is very much easy to find out the diseases. But sometimes people wouldn't able to reach a hospital or any diagnostic center in a short time and it is also very much costly for most people especially for developing country. In that scenario, we proposed a prototype in this paper by which we can recognize the problem urgently and at a low cost. Mainly this is an image processing technique. Using color segmentation technique with SVM classifier, our proposed system can recognize several types of skin diseases based on some feature extraction. This method efficiently recognizes eight different skin diseases with an accuracy rate of percentage is 94.79%. Our recommended model is so simple, fast, and requires any kinds of programmable devices like desktop, android phones, tabs, IOS, and so on.

Keywords
Machine vision , performance metric , recognition , SVM , skin diseases , classification
Journal or Conference Name
2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS)
Publication Year
2021
Indexing
scopus