文章基本信息

标题：Human Identity Recognition Using Ear Lobes Geometric Features
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作者：Syed Adnan Ahmer ; Payal Lohi ; Ruhi Shende 等
期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2016
卷号：5
期号：6
页码：16749-16752
DOI：10.18535/ijecs/v5i6.02
出版社：IJECS
摘要：Verification of person by means of Biometrics can be uniquely identified by one or more biological traits of that person. These unique identifiers include eye pattern, hand pattern, fingerprints, earlobe geometry, retinas, DNA, voice waves and signatures. Recent research in biometrics field has done into finding more ways to identify someone through different gaits proposed. Among many, earlobe biometrics is the stable one considered in the light of aging of Human bodies. As others earlobes geometry does not change with time and emotions. Geometric features considered in earlobe biometrics are ears height, corresponding angles, and inner ears curve and reference line cut points. Random orientation is performed and it shows greater accuracy than previous model. The recognition accuracy is increased by training images in databases. This class of passive identification is ideal for biometrics because the features are robust and can be reliably extracted from distance
关键词：Edge Detection; Nearest Neighbor; Geometric Features; KNN Algorithm; Blob Detection algorithm