Download Biometric systems: technology, design, and performance by James L. Wayman, Anil K. Jain, Davide Maltoni, Dario Maio PDF

By James L. Wayman, Anil K. Jain, Davide Maltoni, Dario Maio

This booklet offers practitioners with an outline of the rules & tools had to construct trustworthy biometric platforms. It covers three major issues: key biometric applied sciences, checking out & administration matters, & the felony and procedure issues of biometric structures for private verification/identification. It specializes in the four most generally used applied sciences - speech, fingerprint, iris & face reputation. It comprises: · In-depth insurance of the technical and useful stumbling blocks that are usually overlooked via software builders & approach integrators & which bring about shortfalls among anticipated and real functionality; · special guidance on biometric method overview; · Protocols & benchmarks so one can enable builders to match functionality & song process advancements. Biometric structures - know-how, layout and function overview is meant as a reference ebook for somebody desirous about the layout, administration or implementation of biometric structures.

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Woods, Speaker authentication and identification: a comparison of spectrographic and auditory presentation of speech material. J. Acoust. Soc. , 44, 596–607, 1968. [25] B. Atal, Automatic recognition of speakers from their voices. Proc. IEEE, 64(4), 460–474, 1976. [26] A. Rosenberg, Automatic speaker recognition: a review. Proc. IEEE, 64(4), 475–487, 1976. [27] M. Trauring, Automatic comparison of finger-ridge patterns. Nature, 197, 938–940, 1963. [28] M. Trauring, On the automatic comparison of finger-ridge patterns.

5 Graphical representation (lateral view and top view) of the Gabor filter defined by the parameters θ = 135°, f = 1/5, σx = σy = 3 [21]. 4)). To contextually filter a fingerprint image using Gabor filters, the four parameters (θ, f, σx, σy) must be specified. Obviously, the frequency, f, of the filter is completely determined by the local ridge frequency, and the orientation, θ, is determined by the local ridge orientation. The selection of the values σx and σy involves a trade-off. The larger the values, the more robust the filters are to the noise in the fingerprint image, but are also the more likely they are to create spurious ridges and valleys.

An enhancement algorithm built upon a model of fingerprint structure can be useful for the enhancement of fingerprints, but it is also important to understand that there are some non-fingerprint properties of digitized fingerprint images that need to be dealt with. The first is that inked fingerprint images may have variations in intensity due to the inking process. The ink may be absent or less dense in some areas or over the entire print. The fingerprint image may also have smudges (blobs) in some areas or over the entire print due to excessive ink.

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