手静脉图像大ROI提取新技术

Marlina Yakno, J. Mohamad-Saleh, B. A. Rosdi
{"title":"手静脉图像大ROI提取新技术","authors":"Marlina Yakno, J. Mohamad-Saleh, B. A. Rosdi","doi":"10.1109/ICBAPS.2015.7292223","DOIUrl":null,"url":null,"abstract":"Region of Interest (ROI) extraction is a crucial step in automatic hand vein biometric and biomedical systems. The aim of ROI extraction is to decide which part of the image is suitable for hand vein feature extraction. The majority vein patterns sometimes can be determined at different locations; left, right and centre of the back of hand. The existing methods have not been able to extract more vein patterns at the right and left borders of the ROI. This paper proposes a hand vein ROI extraction method which is robust at avoiding loss of vein patterns information along the right and left borders of the ROI. First, we determine the threshold value, which will be used to segment the hand region. Second, the hand image is traced using boundary tracing. Third, the Euclidean distance is measured between reference point and hand boundary. Fourth, the distribution diagrams are constructed for the feature points selection. Finally, four coordinates are determined prior to ROI extraction. The experimental results show that the proposed method can extract ROI more accurately and effectively compared with other methods.","PeriodicalId":243293,"journal":{"name":"2015 International Conference on BioSignal Analysis, Processing and Systems (ICBAPS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"New technique for larger ROI extraction of hand vein images\",\"authors\":\"Marlina Yakno, J. Mohamad-Saleh, B. A. Rosdi\",\"doi\":\"10.1109/ICBAPS.2015.7292223\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Region of Interest (ROI) extraction is a crucial step in automatic hand vein biometric and biomedical systems. The aim of ROI extraction is to decide which part of the image is suitable for hand vein feature extraction. The majority vein patterns sometimes can be determined at different locations; left, right and centre of the back of hand. The existing methods have not been able to extract more vein patterns at the right and left borders of the ROI. This paper proposes a hand vein ROI extraction method which is robust at avoiding loss of vein patterns information along the right and left borders of the ROI. First, we determine the threshold value, which will be used to segment the hand region. Second, the hand image is traced using boundary tracing. Third, the Euclidean distance is measured between reference point and hand boundary. Fourth, the distribution diagrams are constructed for the feature points selection. Finally, four coordinates are determined prior to ROI extraction. The experimental results show that the proposed method can extract ROI more accurately and effectively compared with other methods.\",\"PeriodicalId\":243293,\"journal\":{\"name\":\"2015 International Conference on BioSignal Analysis, Processing and Systems (ICBAPS)\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on BioSignal Analysis, Processing and Systems (ICBAPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICBAPS.2015.7292223\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on BioSignal Analysis, Processing and Systems (ICBAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBAPS.2015.7292223","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

感兴趣区域(ROI)提取是自动手静脉生物识别和生物医学系统的关键步骤。ROI提取的目的是决定图像的哪一部分适合进行手静脉特征提取。多数脉型有时可以在不同位置确定;手背的左,右,中间。现有的方法无法在ROI的左右边界提取更多的静脉模式。本文提出了一种手部静脉感兴趣点提取方法,该方法鲁棒性强,避免了感兴趣点左右边界静脉模式信息的丢失。首先,我们确定阈值,该阈值将用于手部区域的分割。其次,利用边界跟踪技术对手图像进行跟踪。第三,测量参考点与手边界之间的欧氏距离。第四,构造特征点分布图,进行特征点选择。最后,在ROI提取之前确定四个坐标。实验结果表明,与其他方法相比,该方法可以更准确有效地提取ROI。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
New technique for larger ROI extraction of hand vein images
Region of Interest (ROI) extraction is a crucial step in automatic hand vein biometric and biomedical systems. The aim of ROI extraction is to decide which part of the image is suitable for hand vein feature extraction. The majority vein patterns sometimes can be determined at different locations; left, right and centre of the back of hand. The existing methods have not been able to extract more vein patterns at the right and left borders of the ROI. This paper proposes a hand vein ROI extraction method which is robust at avoiding loss of vein patterns information along the right and left borders of the ROI. First, we determine the threshold value, which will be used to segment the hand region. Second, the hand image is traced using boundary tracing. Third, the Euclidean distance is measured between reference point and hand boundary. Fourth, the distribution diagrams are constructed for the feature points selection. Finally, four coordinates are determined prior to ROI extraction. The experimental results show that the proposed method can extract ROI more accurately and effectively compared with other methods.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Decrease alpha waves in depression: An electroencephalogram(EEG) study Performance evaluation of automated lung segmentation for High Resolution Computed Tomography (HRCT) thorax images Initial result of body earthing on student stress performance Cardioid graph based ECG biometric using compressed QRS complex Subnanosecond pulsed intense electromagnetic field radiators for non-invasive cancer treatment
×
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