基于几何特征提取的耳朵生物识别

M. Choraś
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引用次数: 158

摘要

事实证明,生物识别方法比传统的人体识别方法更有效、更自然、更容易使用。事实上,只有生物识别方法才能真正识别人类,而不是他们拥有的钥匙和卡片或他们应该记住的密码。生物识别技术的未来必然是基于图像分析的系统,因为数据采集非常简单,只需要摄像头、扫描仪或传感器。更重要的是,这些方法可以是被动的,这意味着用户不必主动参与整个过程,或者实际上甚至不知道识别过程的发生。人体识别系统有许多可能的数据源,但生理生物识别技术似乎比基于人类行为的方法有许多优势。对于这种被动的生理生物识别系统来说,最有趣的人体解剖部位是面部和耳朵。这两种方法都包含大量独特的特征,可以识别许多用户,并且肯定会在许多应用中实现高效的生物识别系统。本文介绍了耳生物识别技术,并介绍了耳生物识别技术相对于人脸生物识别技术在被动人体识别系统中的优势。在此基础上,提出了从人耳图像中提取特征的几何方法,以实现人的身份识别。
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Ear Biometrics Based on Geometrical Feature Extraction
Biometrics identification methods proved to be very efficient, more natural and easy for users than traditional methods of human identification. In fact, only biometrics methods truly identify humans, not keys and cards they posses or passwords they should remember. The future of biometrics will surely lead to systems based on image analysis as the data acquisition is very simple and requires only cameras, scanners or sensors. More importantly such methods could be passive, which means that the user does not have to take active part in the whole process or, in fact, would not even know that the process of identification takes place. There are many possible data sources for human identification systems, but the physiological biometrics seem to have many advantages over methods based on human behaviour. The most interesting human anatomical parts for such passive, physiological biometrics systems based on images acquired from cameras are face and ear. Both of those methods contain large volume of unique features that allow to distinctively identify many users and will be surely implemented into efficient biometrics systems for many applications. The article introduces to ear biometrics and presents its advantages over face biometrics in passive human identification systems. Then the geometrical method of feature extraction from human ear images in order to perform human identification is presented.
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