Skin Disease Detection Using Image Processing Technique

Authors

  • Salman Muneer
  • Umar Hanif bu
  • Muhammad Rizwan Ullah Siddiqui Department of Health, Okara
  • Nasir Abbas WHO
  • Shahzad Amir Department of Health, Okara
  • Komal Arshad Department of Health, Okara

Keywords:

Skin diseases, Image Processing, Convolutional Neural Network, classification

Abstract

Skin is the most important part of human body which protects our internal part of our body to any injury. However this important part of human body frequently suffered from many known and unknown illness. The procedure for diagnosing and treating a skin disease involves a medical professional but due to the lack of medical facilities, many people around the world experience the side effects of many real skin infections. Detecting of skin diseases at an early period has most significant role to handle the infection. So that’s why we proposed a system which is based on computer technology to detect the symptom in early stages. We developed a system which identifies the disease based on input symptoms. In this article we utilize the convolutional neural organization strategy to analyze skin diseases. The raw images taken from the digital camera have been given to the input of Convolutional Neural Network and then system will be trained and tested by these images. Our proposed system identifies three different kinds of skin infections which are melanoma, Eczema and Psoriasis.

Downloads

Published

2022-03-31 — Updated on 2022-04-20

How to Cite

Salman, Hanif, U., Siddiqui, M. R. U. ., Abbas, N., Amir, S. ., & Arshad, K. . (2022). Skin Disease Detection Using Image Processing Technique. Journal of NCBAE, 1(1). Retrieved from https://jncbae.com/index.php/home3/article/view/8

Issue

Section

Articles