基于人脸素描图像的虹膜和眼睑高效检测

Q4 Computer Science
Tan Boonchuan, S. Setumin, Abduljalil Radman, S. A. Suandi
{"title":"基于人脸素描图像的虹膜和眼睑高效检测","authors":"Tan Boonchuan, S. Setumin, Abduljalil Radman, S. A. Suandi","doi":"10.5565/REV/ELCVIA.1044","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a simple yet effective technique for an automatic iris and eyelids detection method for facial sketch images. Our system uses Circular Hough Transformation (CHT) algorithm for iris localization process and a low level grayscale analysis for eyelids contour segmentation procedure. We limit the input face for the system to facial sketch photos with frontal pose, illumination invariant, neutral expression and without occlusions. CUHK and IIIT-D sketch databases are used to acquire the experimental results. As to validate the proposed algorithm, experiments on ground truth for iris and eyelids segmentation, which are prepared at our lab, is conducted. The iris segmentation from the proposed method gives the best accuracy of 92.93 and 86.71 based on F-measure evaluation for IIIT-D and CUHK, respectively. For eyelids segmentation, on the other hand, the proposed algorithm achieves an average of 4 standard deviation which indicates the closeness of proposed method to ground truth.","PeriodicalId":38711,"journal":{"name":"Electronic Letters on Computer Vision and Image Analysis","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Efficient Iris and Eyelids Detection from Facial Sketch Images\",\"authors\":\"Tan Boonchuan, S. Setumin, Abduljalil Radman, S. A. Suandi\",\"doi\":\"10.5565/REV/ELCVIA.1044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a simple yet effective technique for an automatic iris and eyelids detection method for facial sketch images. Our system uses Circular Hough Transformation (CHT) algorithm for iris localization process and a low level grayscale analysis for eyelids contour segmentation procedure. We limit the input face for the system to facial sketch photos with frontal pose, illumination invariant, neutral expression and without occlusions. CUHK and IIIT-D sketch databases are used to acquire the experimental results. As to validate the proposed algorithm, experiments on ground truth for iris and eyelids segmentation, which are prepared at our lab, is conducted. The iris segmentation from the proposed method gives the best accuracy of 92.93 and 86.71 based on F-measure evaluation for IIIT-D and CUHK, respectively. For eyelids segmentation, on the other hand, the proposed algorithm achieves an average of 4 standard deviation which indicates the closeness of proposed method to ground truth.\",\"PeriodicalId\":38711,\"journal\":{\"name\":\"Electronic Letters on Computer Vision and Image Analysis\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronic Letters on Computer Vision and Image Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5565/REV/ELCVIA.1044\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronic Letters on Computer Vision and Image Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5565/REV/ELCVIA.1044","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 4

摘要

在本文中,我们提出了一种简单而有效的人脸草图图像虹膜和眼睑自动检测方法。我们的系统使用循环霍夫变换(CHT)算法进行虹膜定位过程,并使用低级别灰度分析进行眼睑轮廓分割过程。我们将系统的输入人脸限制为具有正面姿态、照明不变、中性表情和无遮挡的人脸草图照片。使用中大和IIIT-D草图数据库获取实验结果。为了验证所提出的算法,我们在实验室进行了虹膜和眼睑分割的地面实况实验。基于IIIT-D和中大的F-measure评估,该方法的虹膜分割分别给出了92.93和86.71的最佳精度。另一方面,对于眼睑分割,所提出的算法平均达到4个标准差,这表明所提出的方法与地面实况的接近性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient Iris and Eyelids Detection from Facial Sketch Images
In this paper, we propose a simple yet effective technique for an automatic iris and eyelids detection method for facial sketch images. Our system uses Circular Hough Transformation (CHT) algorithm for iris localization process and a low level grayscale analysis for eyelids contour segmentation procedure. We limit the input face for the system to facial sketch photos with frontal pose, illumination invariant, neutral expression and without occlusions. CUHK and IIIT-D sketch databases are used to acquire the experimental results. As to validate the proposed algorithm, experiments on ground truth for iris and eyelids segmentation, which are prepared at our lab, is conducted. The iris segmentation from the proposed method gives the best accuracy of 92.93 and 86.71 based on F-measure evaluation for IIIT-D and CUHK, respectively. For eyelids segmentation, on the other hand, the proposed algorithm achieves an average of 4 standard deviation which indicates the closeness of proposed method to ground truth.
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
Electronic Letters on Computer Vision and Image Analysis
Electronic Letters on Computer Vision and Image Analysis Computer Science-Computer Vision and Pattern Recognition
CiteScore
2.50
自引率
0.00%
发文量
19
审稿时长
12 weeks
×
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:604180095
Book学术官方微信