Dermatological disease detection using image processing and artificial neural network

Rahat Yasir, M. A. Rahman, Nova Ahmed
{"title":"Dermatological disease detection using image processing and artificial neural network","authors":"Rahat Yasir, M. A. Rahman, Nova Ahmed","doi":"10.1109/ICECE.2014.7026918","DOIUrl":null,"url":null,"abstract":"Skin diseases are among the most common health problems worldwide. In this article we proposed a method that uses computer vision based techniques to detect various kinds of dermatological skin diseases. We have used different types of image processing algorithms for feature extraction and feed forward artificial neural network for training and testing purpose. The system works on two phases- first pre-process the colour skin images to extract significant features and later identifies the diseases. The system successfully detects 9 different types of dermatological skin diseases with an accuracy rate of 90%.","PeriodicalId":335492,"journal":{"name":"8th International Conference on Electrical and Computer Engineering","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"92","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"8th International Conference on Electrical and Computer Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECE.2014.7026918","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 92

Abstract

Skin diseases are among the most common health problems worldwide. In this article we proposed a method that uses computer vision based techniques to detect various kinds of dermatological skin diseases. We have used different types of image processing algorithms for feature extraction and feed forward artificial neural network for training and testing purpose. The system works on two phases- first pre-process the colour skin images to extract significant features and later identifies the diseases. The system successfully detects 9 different types of dermatological skin diseases with an accuracy rate of 90%.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于图像处理和人工神经网络的皮肤病检测
皮肤病是世界上最常见的健康问题之一。本文提出了一种利用计算机视觉技术检测各种皮肤病的方法。我们使用不同类型的图像处理算法进行特征提取,并使用前馈人工神经网络进行训练和测试。该系统分两个阶段工作——首先对彩色皮肤图像进行预处理,提取重要特征,然后识别疾病。该系统成功检测出9种不同类型的皮肤病,准确率达到90%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Empirical prediction of optical transitions in metallic armchair SWCNTs Dynamics of fullerene self-insertion into carbon nanotubes in water Diffusion tensor based global tractography of human brain fiber bundles Biomass quality analysis for power generation Video-based affinity group detection using trajectories of multiple subjects
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1