Analysis and Detection of Dermatitis Diseases using Image Segmentation Algorithm Method.

Prafulla Aerkewar , Dr. G. H. Agrawal

Segmentation, Disease, Dermatitis Lesion, Patch,, Leprosy, Vitiligo, Psoriasis, Feature Extraction, Feature Selection, Entropy, Autocorrelation

The aim to publish this research paper to classify dermatitis disease using new an advanced technique of image segmentation called k-means clustering method. The process of clustering image segmentation method extract different features of input test image of dermatitis disease and compare with database images features values. This method suggest appropriate procedure such that the all dermatitis disease having skin lesion on body are classified in to four category using k-means image segmentation and nntool of Matlab. Through the image segmentation technique and nntool can be analyze and study the segmentation properties of skin lesions occurs in dermatitis disease. A skin lesion is a superficial growth or patch of the skin that does not resemble the area surrounding it. It have also been proposed that which are suitable for the processing of various images for different types of patches for various skin diseases. The skin lesion in different dermatitis diseases are different in appearance and have different properties though they looks similar in some circumstances. The main objective to classify the lesions of different dermatitis diseases based on its twelve parameters like contrast, Energy, Homogeneity etc where it would be able to classify the similar patch in to different disease.

Published Paper   E-Certificate

"Analysis and Detection of Dermatitis Diseases using Image Segmentation Algorithm Method.", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.3, Issue 7, page no.68-72, July-2018, Available :https://ijnrd.org/papers/IJNRD1807012.pdf

Volume 3 Issue 7, July-2018

Pages : 68-72

Paper Reg. ID: IJNRD_180132

Published Paper Id: IJNRD1807012

Downloads: 000118812

Research Area: Engineering

Country: Nagpur, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD1807012

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD1807012

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition