By David Zhang
Automatic own authentication utilizing biometric details is changing into extra crucial in functions of public defense, entry keep an eye on, forensics, banking, and so forth. Many varieties of biometric authentication suggestions were built in line with diversified biometric features. even if, lots of the actual biometric popularity options are in keeping with dimensional (2D) photographs, although human features are 3 dimensional (3D) surfaces. lately, 3D thoughts were utilized to biometric functions equivalent to 3D face, 3D palmprint, 3D fingerprint, and 3D ear attractiveness. This e-book introduces 4 average 3D imaging tools, and offers a few case reviews within the box of 3D biometrics. This e-book additionally contains many effective 3D characteristic extraction, matching, and fusion algorithms. those 3D imaging tools and their purposes are given as follows: - unmarried view imaging with line structured-light: 3D ear identity - unmarried view imaging with multi-line structured-light: 3D palmprint authentication - unmarried view imaging utilizing simply 3D digicam: 3D hand verification - Multi-view imaging: 3D fingerprint attractiveness 3D Biometrics: structures and Applications is a complete creation to either theoretical matters and useful implementation in 3D biometric authentication. it's going to function a textbook or as an invaluable reference for graduate scholars and researchers within the fields of computing device technology, electric engineering, platforms technology, and data expertise. Researchers and practitioners in and R&D laboratories engaged on safety process layout, biometrics, immigration, legislations enforcement, regulate, and trend reputation also will locate a lot of curiosity during this book.
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Extra resources for 3D Biometrics: Systems and Applications
In: Proceedings of media processors 2002, SPIE electronic imaging. 7800 Yalla V, Hassebrook LG (2005) Very-high resolution 3d surface scanning using multi-frequency phase measuring profilometry. Spaceborne sensors II, SPIE’s defense and security symposium, vol 5798–09, pp 1234–1240. 603832 Yan P, Bowyer KW (2007) Biometric recognition using 3D ear shape. IEEE Trans Pattern Anal Mach Intell 29(8):1297–1308. 1067 Yang JC, Everett M, Buehler C, McMillan L (2002a) A real-time distributed light field camera.
2001); Naemura et al. (Naemura et al. 2002) constructed a system of 16 cameras for realtime rendering. Several large arrays consisting of tens of cameras have also been built, such as the Stanford multi-camera array, the MIT distributed light field camera and the CMU 3D room. These three systems have 128, 64 and 49 cameras, respectively (Wilburn et al. 2002; Yang et al. 2002b; Kanade et al. 1998). In the above camera arrays, those with a small number of cameras can usually achieve real-time rendering.
It has been written for a professional audience of both researchers and practitioners within industry, and is also ideal as an informative text for graduate students in computer science and engineering. 1 Introduction In today’s complex, geographically mobile, increasingly electronically wired information society, the problem of verifying an individual identity continues to pose a great challenge. Conventional technology using Personal Identification Numbers (PIN) or passwords, often in conjunction with plastic cards, is neither convenient nor particularly secure.