Enhancement of Vascular Patterns in Palm Images Using Various Image Enhancement Techniques for Person Identification

M. Rajalakshmi, K. Annapurani
{"title":"Enhancement of Vascular Patterns in Palm Images Using Various Image Enhancement Techniques for Person Identification","authors":"M. Rajalakshmi, K. Annapurani","doi":"10.1142/s0219467822500322","DOIUrl":null,"url":null,"abstract":"Image classification is a complicated process of classifying an image based on its visual representation. This paper portrays the need for adapting and applying a suitable image enhancement and denoising technique in order to arrive at a successful classification of data captured remotely. Biometric properties that are widely explored today are very important for authentication purposes. Noise may be the result of incorrect vein detection in the accepted image, thus explaining the need for a better development technique. This work provides subjective and objective analysis of the performance of various image enhancement filters in the spatial domain. After performing these pre-processing steps, the vein map and the corresponding vein graph can be easily obtained with minimal extraction steps, in which the appropriate Graph Matching method can be used to evaluate hand vein graphs thus performing the person authentication. The analysis result shows that the image enhancement filter performs better as an image enhancement filter compared to all other filters. Image quality measures (IQMs) are also tabulated for the evaluation of image quality.","PeriodicalId":177479,"journal":{"name":"Int. J. Image Graph.","volume":"105 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Image Graph.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s0219467822500322","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Image classification is a complicated process of classifying an image based on its visual representation. This paper portrays the need for adapting and applying a suitable image enhancement and denoising technique in order to arrive at a successful classification of data captured remotely. Biometric properties that are widely explored today are very important for authentication purposes. Noise may be the result of incorrect vein detection in the accepted image, thus explaining the need for a better development technique. This work provides subjective and objective analysis of the performance of various image enhancement filters in the spatial domain. After performing these pre-processing steps, the vein map and the corresponding vein graph can be easily obtained with minimal extraction steps, in which the appropriate Graph Matching method can be used to evaluate hand vein graphs thus performing the person authentication. The analysis result shows that the image enhancement filter performs better as an image enhancement filter compared to all other filters. Image quality measures (IQMs) are also tabulated for the evaluation of image quality.
利用各种图像增强技术增强手掌图像中的血管模式,用于人物识别
图像分类是基于图像的视觉表征对图像进行分类的复杂过程。本文描述了适应和应用合适的图像增强和去噪技术的必要性,以便对远程捕获的数据进行成功的分类。目前广泛探索的生物特征特性对于身份验证非常重要。噪声可能是接受图像中不正确的静脉检测的结果,因此解释了需要更好的显影技术。本文对各种图像增强滤波器在空间域中的性能进行了主观和客观的分析。在完成这些预处理步骤后,可以用最少的提取步骤轻松地获得静脉图和相应的静脉图,其中可以使用适当的图匹配方法对手部静脉图进行评估,从而进行人的身份验证。分析结果表明,与所有其他滤波器相比,图像增强滤波器具有更好的图像增强性能。图像质量度量(iqm)也被制成表格用于评估图像质量。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信