Biometrics: Proving Ground for Image and Pattern Recognition

A.K. Jain
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引用次数: 6

Abstract

The emerging requirements of reliable and highly accurate personal identification in a number of government and commercial applications (e.g., international border crossings, access to buildings, laptops and mobile phones) have served as an impetus for a tremendous growth in biometric recognition technology. Biometrics refers to the automatic recognition of an individual by using anatomical or behavioral traits associated with that person. By using biometrics, it is possible to recognize a person based on who you are, rather than by what you possess (e.g., an ID card) or what you remember (e.g., a password). Most of the authentication systems based on passwords (knowledge-based security) and ID cards (token-based security) can be easily breached when a password is divulged to an unauthorized user or a card is stolen by an impostor. Biometric systems have addressed the security problems that plague traditional verification systems because they make use of a person's fingerprint, hand shape, iris, face and voice that are supposed to be unique to that person. Besides bolstering security, biometric systems also enhance user convenience by alleviating the need to design and remember multiple complex passwords. No wonder large scale systems have been deployed in such diverse applications as US-VISIT and entry to Disney Park, Orlando. The revenues for the global biometric recognition market are projected to grow from about US $2.1 billion in 2006 to US $5.7 billion in 2010. In spite of the fact that automatic biometric recognition systems based on fingerprints (called AFIS) have been used by law enforcement agencies worldwide for over 40 years, biometric recognition continues to remain a very difficult pattern recognition problem. A biometric system has to contend with problems related to noisy images (failure to enroll), lack of distinctiveness (finite error rate), large intra-class variations (false reject), and spoof attacks (system security). This talk will present an overview of biometrics, its advantages and limitations, state-of-the-art error rates and current research in sensor design, representation, fusion and security issues.
生物计量学:图像和模式识别的试验场
在许多政府和商业应用(例如,国际边境口岸、进入建筑物、笔记本电脑和移动电话)中出现的对可靠和高度准确的个人识别的新要求,推动了生物识别技术的巨大增长。生物识别技术是指通过使用与该人相关的解剖学或行为特征来自动识别个人。通过使用生物识别技术,可以根据你是谁来识别一个人,而不是根据你拥有什么(如身份证)或你记得什么(如密码)。大多数基于密码(基于知识的安全性)和身份证(基于令牌的安全性)的身份验证系统在密码泄露给未经授权的用户或卡被冒名顶替者窃取时很容易被破坏。生物识别系统解决了困扰传统验证系统的安全问题,因为它们利用了一个人的指纹、手型、虹膜、面部和声音,这些应该是这个人独有的。除了加强保安外,生物识别系统亦减轻使用者设计和记忆多个复杂密码的需要,从而提高使用者的便利性。难怪大型系统已经部署在各种应用中,如US-VISIT和奥兰多迪斯尼公园的入口。全球生物识别市场的收入预计将从2006年的21亿美元增长到2010年的57亿美元。尽管基于指纹的自动生物识别系统(AFIS)已经在世界各地的执法机构中使用了40多年,但生物识别仍然是一个非常困难的模式识别问题。生物识别系统必须应对与噪声图像(注册失败)、缺乏独特性(有限错误率)、大的类内变化(误拒)和欺骗攻击(系统安全性)相关的问题。本讲座将介绍生物识别技术的概况,它的优点和局限性,最新的误差率和当前在传感器设计,表示,融合和安全问题方面的研究。
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