硕士生导师
个人信息Personal Information
学历：博士研究生毕业
学位：工学博士学位
办公地点：犀浦3号教学楼31529
毕业院校：四川大学
学科：电子信息. 软件工程. 计算机应用技术
所在单位：计算机与人工智能学院
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Finger vein ROI extraction based on robust edge detection and flexible sliding window
影响因子：1.261
DOI码：10.1142/s0218001418560025
所属单位：西南交通大学
发表刊物：Dongming Tang, Zhangyou Chen
关键字：Biometric recognitionfinger vein recognitionregion of interestfinger vein image
摘要：An accurate region of interest extraction (ROI) plays an important role for both finger vein recognition systems and finger vein-based cryptography systems. In order to localize the rectangle ROI accurately, the edges of the finger and a line in the finger joint region should be detected accurately as a reference position. Because most of the existing finger edge detection methods do not work well, a robust finger edge detection method is proposed in this paper. An inner line of the finger is first detected to divide the finger vein image by two parts, after that two edge detection templates and a series of technologies such as interpolation, fit, etc. are used to detect and fix the wrong edges of the finger. Furthermore, considering that the shapes of the brighter finger joint region are irregular, multiple sliding windows including rectangle, disk, diamond and ellipse are generated, respectively to detect the reference line of the finger joint. Finally, a contour similarity distance-based method is introduced to evaluate the performance of various sliding windows. The experimental results show that the proposed edge detection method can 100% successfully detect the edges of the fingers in our finger vein image database. And for various detection windows, the ellipse window is more suitable for the detection of the finger joint reference line. So, the proposed ROI extraction method for finger vein images has a better overall performance compared with the other methods.
合写作者：Dongming Tang, Zhangyou Chen
第一作者：Mingwen Wang
论文类型：学术论文
通讯作者：Mingwen Wang
论文编号：20173504079158
学科门类：工学
一级学科：计算机科学与技术
卷号：32
期号：4
ISSN号：0218-0014
是否译文：否
发表时间：2017-08-22