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We proposed an image processing-based method to detect skin diseases. This method takes the digital image of disease effect skin area and then uses image analysis to identify the type of disease. Our proposed approach is simple, fast, and does not require expensive equipment, it can run on any device which has internet access. Just upload the im…

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Skin Disease Analysis

Skin diseases are more common than other diseases. Skin diseases may be caused by fungal infection, bacteria, allergy, or viruses, etc. They have a serious impact on people’s life and health. Current research proposes an efficient approach to identify singular type of skin diseases. It is necessary to develop automatic methods in order to increase the accuracy of diagnosis for multi type skin diseases. So, image processing techniques help to build automated screening system for dermatology at an initial stage. The experimental results demonstrate the effectiveness and feasibility of the proposed method.

We proposed an image processing-based method to detect skin diseases. This method takes the digital image of disease effect skin area, and then uses image analysis to identify the type of disease. Our proposed approach is simple, fast and does not require expensive equipment, it can run on any device which has internet access. Just upload the image of your skin and check whether you have any skin disease or not.

Requirements

  1. Browser
  2. Internet connection

Demo

Built with

For backend : Python3 , Azure Function For frontend: Javascript, Html, CSS

How to deploy Azure function

Open folder "Azure Projects" in Visual Studio and then please refer to this article https://docs.microsoft.com/en-us/azure/azure-functions/functions-develop-vs

API

After deployment, 'Visual Studio Code' will give you a HTTP API which you can update in "Webpage/js/upload.js" on line no 14

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We proposed an image processing-based method to detect skin diseases. This method takes the digital image of disease effect skin area and then uses image analysis to identify the type of disease. Our proposed approach is simple, fast, and does not require expensive equipment, it can run on any device which has internet access. Just upload the im…

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