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Title of Journal: Neural Comput Applic

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Abbravation: Neural Computing and Applications

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Springer-Verlag

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DOI

10.1007/bf00588408

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1433-3058

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Newborn footprint recognition using orientation fe

Authors: Wei Jia HaiYang Cai Jie Gui RongXiang Hu YingKe Lei XiaoFeng Wang
Publish Date: 2011/02/05
Volume: 21, Issue: 8, Pages: 1855-1863
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Abstract

Newborn and infant personal authentication is a critical issue for hospital birthing centers and other institutions where multiple births occur which has not been well studied in the past In this paper we propose a novel online newborn personal authentication system for this issue based on footprint recognition Compared with traditional offline footprinting scheme the proposed system can capture digital footprint images with high quality We also develop a preprocessing method for orientation and scale normalization In this way a coordinate system is defined to align the images and a region of interest ROI is cropped In recognition stage four orientation featurebased approaches Ordinal Code BOCV Competitive Code and Robust Line Orientation Code are exploited for recognition A newborn footprint database is established to examine the performance of the proposed system and promising experimental results demonstrate the effectiveness of the proposed systemThis work was supported by the grants of the National Science Foundation of China Nos 60705007 61005010 60805021 60975005 the grant of the Knowledge Innovation Program of the Chinese Academy of Sciences Y023A11292 Y023A61121 the grant of China Postdoctoral Science Foundation No 20100480708 the grant of the Key Scientific Research Foundation of Education Department of Anhui Province No KJ2010A289 and the grant of Scientific Research Foundation for Talents of Hefei University No 11RC05

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