Titlebook: Automatic Fingerprint Recognition Systems; Nalini Ratha,Ruud Bolle Book 2004 Springer Science+Business Media New York 2004 algorithms.biom

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Error Rates for Human Latent Fingerprint Examiners,ently, this evidence has been accepted by the courts as infallibly accurate. We review four kinds of available data about the accuracy of fingerprint comparisons made by human latent fingerprint examiners: anecdotal FBI data; published data on the accuracy of consensus fingerprint comparisons made b

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Generation of Synthetic Fingerprint Image Databases,ch in some countries prohibits the diffusion of such personal information. This chapter describes the SFINGE (acronym for Synthetic FINgerprint GEnerator) approach, developed by the BIOLAB team, which can be used to create, at zero cost, large fingerprint databases. The synthesis of each master fing

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Fingerprint Image Compression and the Wavelet Scalar Quantization Specification,nts of those images. In response to this need, the FBI developed a fingerprint compression specification, called the wavelet scalar quantization (WSQ). As the name suggests, the specification is based on wavelet compression. In this chapter, we review the WSQ specification and discuss its most impor

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Fingerprint Quality Assessment,r for seeking a better representation of the signal or for subjecting the poor signal to alternative methods of processin g (e.g., enhancement [9]). In this chapter,. we explore a definition of the quality of fingerprint impressions and present detailed algorithms to measure image quality. The propo

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Feature Extraction in Fingerprint Images,fingerprint image be transformed into a minutiae map. This transformation generally includes the following steps: preprocessing, ridge direction and ridge width, enhancement, and minutiae detection. This chapter discusses several approaches for extracting the fingerprint feature maps from the spatia

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Fingerprint Matching,n of different matching algorithms can improve the overall matching performance. Fingerprint matching is a challenging pr oblem due to the large intraclass variation between different impressions of the same finger, noise in the fingerprint images, and small interclass variations in fingerprint imag

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Systems Engineering for Large-Scale Fingerprint Systems,res measurement of missed detection and false-alarm error rates. Two parameters are derived from these erro r rates, . and .. Reliability is the probability that the system will report a matching fingerprint given that one is in the database. Selectivity is the average number of false candidates per