On the capacity of a biometrical identification system

Willems, F.M.J.; Kalker, Ton; Goseling, Jasper; Linnartz, Jean-Paul M. G.

doi:10.1109/isit.2003.1228096

Cited by 92 publications

(144 citation statements)

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“…This extends a result of Willems et al [8] showing that the maximum identification rate of a biometrical system is equal to the mutual information between the enrollment and identification observations, see also [4]. A crucial observation to obtain this result is that a set of biometric enrollment vectors can be regarded as a random channel code.…”

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confidence: 80%

Searching methods for biometric identification systems: Fundamental limits

Willems

2009

2009 IEEE International Symposium on Information Theory

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cation rate. This extends a result of Willems et al. [8] showing that the maximum identification rate of a biometrical system is equal to the mutual information between the enrollment and identification observations, see also [4]. A crucial observation to obtain this result is that a set of biometric enrollment vectors can be regarded as a random channel code.In the current manuscript we focus on speeding up the search process, as in [9]. We are not interested in compressing the database as in [5], [6]. We will show that in an informationtheoretical setting quantization methods are optimal.To demonstrate what we mean by quantization, suppose that the system upon observing an individual, first detects to which cluster the individual belongs, and after that decides about the individual itself (two-stage identification). If there are M individuals, an ideal systems will have v'iJ clusters each containing v'iJ individuals. To determine the cluster index v'iJ candidate-clusters can be checked, and then to determine the individual within the cluster, v'iJ refinement-checks are needed. This results in 2v'iJ checks in total, considerably less than the M checks that are required for exhaustive search. In general however individuals can be in more than one cluster, see Fig. 1, and then the number of cluster-checks times the number of refinement-checks exceeds the number of individuals. Here we investigate the fundamental trade-off between cluster-check rate and refinement-check rate.An important point is what we mean by a cluster-check. In principle a cluster-check could correspond to v'iJ subchecks, one for each individual within the cluster. To prevent this, we require the device that makes the cluster-decision to be "ignorant" of the biometric enrollment vectors. Under this assumption an optimal system contains an ignorant device that acts as a vector quantizer.In the next section we present our model of a biometrical identification system based on two-stage identification and we

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confidence: 80%

Searching methods for biometric identification systems: Fundamental limits

Willems

2009

2009 IEEE International Symposium on Information Theory

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“…The proof of this theorem follows a random coding-based strategy similar to one used in [9] and is omitted.…”

Section: Theorem[9]mentioning

confidence: 99%

“…The progress achieved along the former direction was mostly oriented on design of various robust feature extraction techniques and efficient matching strategies [1], [2]. The efforts along the latter one were mostly spent to analyze the achievable identification rates [3] in the formulation of infinite length codeword transmission over the discrete memoryless channel (DMC). Furthermore, several groups of authors analyzed the identification problem within the information-detection framework for various channel and codeword length assumptions [4,5,6].…”

Section: Introductionmentioning

confidence: 99%

Information-theoretic analysis of desynchronization invariant object identification

Koval

Voloshynovskiy

Farhadzadeh

et al. 2011

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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This paper is dedicated to the analysis of object identification under desynchronization distortions. While this class of degradations is almost unavoidable in the functionality of such systems especially at the verification stage via acquisition imperfections, currently available their performance limits do not take its impact into consideration. In this paper we will try to close this gap providing the estimation of the achievable identification rates due to desynchronization distortions. Finally, the impact of the codeword length on the identification performance is justified.Index Terms-Identification of multimedia objects, desynchronization, capacity, probabilities of error.

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“…The identification or the nearest neighbor search is a research problem that simultaneously has emerged in a number of applications such as human biometrics [1], content management (multimedia retrieval) [2], multimedia security (copy detection, content identification and tracking) [3] as well as physical object security [4].…”

Section: Introductionmentioning

confidence: 99%

“…An identification system [1] consists of two main phases: enrollment and identification. In the first phase, the enrollment, feature vectors representing digital contents, humans or physical objects are extracted and stored in a database.…”

Section: Introductionmentioning

confidence: 99%

Fundamental limits of identification: Identification rate, search and memory complexity trade-off

Farhadzadeh

Willems

Voloshynovskiy

2013

2013 IEEE International Symposium on Information Theory

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Abstract-In this paper, we introduce a new generalized scheme to resolve the trade-off between the identification rate, search and memory complexities in large-scale identification systems. The main contribution of this paper consists in a special database organization based on assigning entries of a database to a set of predefined and possibly overlapping clusters, where the cluster representative points are generated based on statistics of both entries of the database and queries. The decoding procedure is accomplished in two stages: At the first stage, a list of clusters related to the query is estimated, then refinement checks are performed to all members of these clusters to produce a unique index at the second stage. The proposed scheme generalizes several practical searching in identification systems as well as makes it possible to approach a new achievable region of searchmemory complexity trade-off.

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On the capacity of a biometrical identification system

Cited by 92 publications

References 1 publication

Searching methods for biometric identification systems: Fundamental limits

Searching methods for biometric identification systems: Fundamental limits

Information-theoretic analysis of desynchronization invariant object identification

Fundamental limits of identification: Identification rate, search and memory complexity trade-off

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