基于强度标记算法的现场可编程门阵列瞳孔检测系统

S. Baskaran, L. Ali, A. Anitharani, E. Rani, N. Nandhagopal
{"title":"基于强度标记算法的现场可编程门阵列瞳孔检测系统","authors":"S. Baskaran, L. Ali, A. Anitharani, E. Rani, N. Nandhagopal","doi":"10.1166/JCTN.2020.9429","DOIUrl":null,"url":null,"abstract":"Pupil detection techniques are an essential diagnostic technique in medical applications. Pupil detection becomes more complex because of the dynamic movement of the pupil region and it’s size. Eye-tracking is either the method of assessing the point of focus (where one sees)\n or the orientation of an eye relative to the head. An instrument used to control eye positions and eye activity is the eye tracker. As an input tool for human-computer interaction, eye trackers are used in research on the visual system, in psychology, psycholinguistics, marketing, and product\n design. Eye detection is one in all the applications in the image process. This is very important in human identification and it will improve today’s identification technique that solely involves the eye detection to spot individuals. This technology is still new, only a few domains\n are applying this technology as their medical system. The proposed work is developing an eye pupil detection method in real-time, stable, using an intensity labeling algorithm. The proposed hardware architecture is designed using the median filter, segmentation using the threshold process,\n and morphology to detect pupil shape. Finally, an intensity Labeling algorithm is done to locate an exact eye pupil region. A Real-time FPGA implementation is done by Altera Quartus II software with cyclone IV FPGA.","PeriodicalId":15416,"journal":{"name":"Journal of Computational and Theoretical Nanoscience","volume":"17 1","pages":"5364-5367"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pupil Detection System Using Intensity Labeling Algorithm in Field Programmable Gate Array\",\"authors\":\"S. Baskaran, L. Ali, A. Anitharani, E. Rani, N. Nandhagopal\",\"doi\":\"10.1166/JCTN.2020.9429\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pupil detection techniques are an essential diagnostic technique in medical applications. Pupil detection becomes more complex because of the dynamic movement of the pupil region and it’s size. Eye-tracking is either the method of assessing the point of focus (where one sees)\\n or the orientation of an eye relative to the head. An instrument used to control eye positions and eye activity is the eye tracker. As an input tool for human-computer interaction, eye trackers are used in research on the visual system, in psychology, psycholinguistics, marketing, and product\\n design. Eye detection is one in all the applications in the image process. This is very important in human identification and it will improve today’s identification technique that solely involves the eye detection to spot individuals. This technology is still new, only a few domains\\n are applying this technology as their medical system. The proposed work is developing an eye pupil detection method in real-time, stable, using an intensity labeling algorithm. The proposed hardware architecture is designed using the median filter, segmentation using the threshold process,\\n and morphology to detect pupil shape. Finally, an intensity Labeling algorithm is done to locate an exact eye pupil region. A Real-time FPGA implementation is done by Altera Quartus II software with cyclone IV FPGA.\",\"PeriodicalId\":15416,\"journal\":{\"name\":\"Journal of Computational and Theoretical Nanoscience\",\"volume\":\"17 1\",\"pages\":\"5364-5367\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational and Theoretical Nanoscience\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1166/JCTN.2020.9429\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Chemistry\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational and Theoretical Nanoscience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1166/JCTN.2020.9429","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Chemistry","Score":null,"Total":0}
引用次数: 0

摘要

瞳孔检测技术是一项重要的医学诊断技术。由于瞳孔区域的动态运动和瞳孔的大小,瞳孔检测变得更加复杂。眼球追踪是一种评估焦点(一个人看到的地方)或眼睛相对于头部的方向的方法。眼球追踪仪是一种用来控制眼球位置和眼球活动的仪器。眼动仪作为人机交互的输入工具,广泛应用于视觉系统、心理学、心理语言学、市场营销和产品设计等领域的研究。眼睛检测是图像处理中的一种应用。这在人类识别中是非常重要的,它将改进目前仅通过眼睛检测来识别个体的识别技术。该技术尚属新兴技术,目前只有少数领域将其应用于医疗系统。提出的工作是开发一种实时,稳定的眼睛瞳孔检测方法,使用强度标记算法。硬件结构采用中值滤波、阈值分割和形态学检测瞳孔形状。最后,利用强度标记算法对瞳孔区域进行精确定位。采用Altera Quartus II软件和cyclone IV FPGA实现实时FPGA。
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
Pupil Detection System Using Intensity Labeling Algorithm in Field Programmable Gate Array
Pupil detection techniques are an essential diagnostic technique in medical applications. Pupil detection becomes more complex because of the dynamic movement of the pupil region and it’s size. Eye-tracking is either the method of assessing the point of focus (where one sees) or the orientation of an eye relative to the head. An instrument used to control eye positions and eye activity is the eye tracker. As an input tool for human-computer interaction, eye trackers are used in research on the visual system, in psychology, psycholinguistics, marketing, and product design. Eye detection is one in all the applications in the image process. This is very important in human identification and it will improve today’s identification technique that solely involves the eye detection to spot individuals. This technology is still new, only a few domains are applying this technology as their medical system. The proposed work is developing an eye pupil detection method in real-time, stable, using an intensity labeling algorithm. The proposed hardware architecture is designed using the median filter, segmentation using the threshold process, and morphology to detect pupil shape. Finally, an intensity Labeling algorithm is done to locate an exact eye pupil region. A Real-time FPGA implementation is done by Altera Quartus II software with cyclone IV FPGA.
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
Journal of Computational and Theoretical Nanoscience
Journal of Computational and Theoretical Nanoscience 工程技术-材料科学:综合
自引率
0.00%
发文量
0
审稿时长
3.9 months
期刊介绍: Information not localized
期刊最新文献
The 'Insertion/Deletion' Polymorphism, rs4340 and Diabetes Risk: A Pilot Study from a Hospital Cohort. Reincluding: Providing Support to Reengage Youth who Truant in Secondary Schools. Eosinophil cationic protein (ECP) correlates with eosinophil cell counts in the induced sputum of elite swimmers. Synergic action of an inserted carbohydrate-binding module in a glycoside hydrolase family 5 endoglucanase. [Prognostic impact of prior cardiopathy in patients hospitalized with COVID-19 pneumonia].
×
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