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Face Biometrics for Personal Identification: Multi-Sensory Multi-Modal Systems (Signals and Communication Technology)

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From time immemorial, the security realm and personal identification task had shown progress by employing technological means like secret knowledge as passwords and Personal Identification Numbers, and by using personal possessions as identity cards and Radio Frequency Identification chips. As opposed to these means which are generally easy targets for circulation and fraud, biometric traits (or modalities) like facial geometry, iris, voice timbre, and biological DNA are universal, difficult to copy, and for most, consistent over time with no expiration date and comfortable to use. The purpose of this book is to provide an up-to-date ample coverage of theoretical and experimental state-of-the-art work as well as new trends and directions in the biometrics field.

The biometrics field – the science of measuring physical properties of human beings – has marked a substantial leap over the past two decades. It will continue to climb, as a result of a strong demand from both the private sector and governmental agencies, on an ever ramping curve until practical objectives are achieved in terms of high accuracy, ease of use, and low-cost. As the cost of biometric sensors – visible, multispectral and thermal imagers, microphones, capacitive, pressure and motion sensors – continues to sink due to higher demand, biometric systems have the tendency to employ more than a single sensor to capture and identify an individual upon as many as nonredundant biometric traits.

While this book covers a range of biometric traits including facial geometry, 3D ear form, fingerprints, vein structure, voice, and gait, its main emphasis is placed on multisensory and multimodal face biometrics algorithms and systems. By “multisensory” we refer to combining data from two or more biometric sensors, such as synchronized reflectance-based and temperature-based face images. Likewise, by “multimodal” biometrics, we refer to fusing two or more biometric modalities, like face images and voice timber. These two multisensory and multimodal aspects, as they pertain to face Biometrics, are covered in details in the course of this book. Reported experimental results support the idea that adequate fusion of complementary biometric data is a step in the right direction to remedy to the limitations of existing uni-sensor and uni-modal biometric systems.

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