Psoriasis Skin Disease Identification Using Support Vector Machine(SVM) Image Classification and Determining the Growth Rate

Psoriasis Skin Disease Identification Using Support Vector Machine(SVM) Image Classification and Determining the Growth Rate TR Thamizhvani Aparna K Ajayan V Sannidhya RJ Hemalatha R Chandrasekaran Abstract

In the Indian population, a larger part is under the subsistence level. Most of the people are living in areas of poor sanitation and have very little access to good medical facilities. From time to time, they don’t have the notice to go to a physician at the absolute time. The condition has been defined as a skin disorder or disease wherever there is a failure to induce the right identification and treatment in time typically ends up in advanced stages. Skin diseases tend to be itchy and cover the body easily. Among them, Psoriasis exists as a chronic inflammatory disease characterized by scaly patches on the skin. The proposed system focuses on SVM segmentation and scaling of 2D processed skin pore images of Psoriasis. The Feature Scaling Technique uses color, contrast, and image texture along with a combination of SVM classification features to diagnose and come up with a treatment solution. This computer-assisted image processing system removes erythematous from the psoriasis image for analysis and determination of growth rate. Therefore, earlier identification cuts back the symptoms of the illness and helps in developing a condition that indulges the strategies to live along with the disease condition called Psoriasis.
08 01 2022 012034 http://dx.doi.org/10.1088/crossmark-policy iopscience.iop.org Psoriasis Skin Disease Identification Using Support Vector Machine(SVM) Image Classification and Determining the Growth Rate Journal of Physics: Conference Series paper Published under licence by IOP Publishing Ltd http://creativecommons.org/licenses/by/3.0/ https://iopscience.iop.org/info/page/text-and-data-mining 10.1088/1742-6596/2318/1/012034 https://iopscience.iop.org/article/10.1088/1742-6596/2318/1/012034 https://iopscience.iop.org/article/10.1088/1742-6596/2318/1/012034/pdf https://iopscience.iop.org/article/10.1088/1742-6596/2318/1/012034/pdf https://iopscience.iop.org/article/10.1088/1742-6596/2318/1/012034 https://iopscience.iop.org/article/10.1088/1742-6596/2318/1/012034/pdf Kalbande 1199 2020 Early Stage Detection of Psoriasis Using Artificial Intelligence and Image Processing International Research Journal of Engineering and Technology (IRJET) Patil 10 664 2020 Skin Disease Detection using Image Processing Technique Venmathi 0490 2019 Image Segmentation based on Markov Random Field Probabilistic Approach International Journal of Creative Research Thoughts Tharangini 6 737 2018 Skin Cancer Detection Using Particle Swarm Optimization Rashid 1 2018 Brain Tumor Detection Using Anisotropic Filtering, SVM Classifier and Morphological Operation from MR Images Eurasip Journal on image and video processing Kubanak 45 2017 The use of hidden Markov models to verify the identity based on facial asymmetry International Journal on Pure and Applied Bioscience Saifudeen 5 436 2017 10.18782/2320-7051.2877 Detection of Progression of Clinical Mastitis in Cows Using Hidden Markov Model Exp Dermatol PubMed Garzorz-Stark 25 767 2016 10.1111/exd.13077 A novel molecular disease classifier for psoriasis and eczema Journal Northern Clinical Isthambul Sarac 3 79 2016 A brief summary of clinical types of psoriasis Zhang 62 2016 SVM Methods in Image Segmentation Comput Methods Programs Biomed Shrivastava 126 98 2016 10.1016/j.cmpb.2015.11.013 Computer-aided diagnosis of psoriasis skin images with HOS, texture and color features: A first comparative study of its kind Human brain mapping Wang 35 4777 2014 10.1002/hbm.22511 Analysis of Spatio-Temporal Brain Imaging Patterns by Hidden Markov Models and Serial MRI Images Sukkar 2845 2012 Disease Progression Modeling Using Hidden Markov Models Kolaman 94 2011 Relativity and contrast enhancement Kato 2 2008 Markov Random Fields in Image Segmentation Bharathi 1917 2021 Identification of Melanoma from Nevus Images Appl. Sci. Lin 10.3390/app11073155 11 3155 2021 Instance Segmentation Based on Deep Convolutional Neural Networks and Transfer Learning for Unconstrained Psoriasis Skin Images