Combining match scores with liveness values in a fingerprint verification system

By Emanuela Marasco, Yaohui Ding, Arun A. Ross. 2012

46 citations recorded by the source corpus.

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Citations in the corpus

Robust multimodal face and fingerprint fusion in the presence of spoofing attacks (2016, methodology): “This initial study is extended in [15] evaluating sequential fusion, classifier fusion, and Bayesian Belief Networks for combining match scores and liveness measures, highlighting the superiority of the latter method for the LivDet2009 dataset but also that accuracy is decreased when taking liveness”
A Survey on Anti-Spooﬁng Schemes for Fingerprint Recognition Systems (2014, background): “[Marasco et al. 2012] proposed four different architectures to perform this fusion.”
Biometric Antispoofing Methods: A Survey in Face Recognition (2014, background): “Although the above methodology would already represent a big advance if it was widely adopted or implemented into a standard, it still opens some new interesting topics for research which have just started to be explored: What is the best way to combine matching and liveness-detection scores [164], ”
Towards anomaly detection for increased security in multibiometric systems: Spoofing-resistant 1-median fusion eliminating outliers (2014, background): “[9] analysed three different types of fusion schemes (sequential, classifier and Bayesian Belief Network (BBN) ) combining match scores and liveness measures (degree of liveness).”
A Bayesian approach for modeling sensor influence on quality, liveness and match score values in fingerprint verification (2013, methodology): “Accordingly, recent studies have combined match scores generated by a fingerprint matcher with liveness values [4], [5] as well as image quality value [6], in order to render a decision on the recognition process.”
Anti-spoofing in Action: Joint Operation with a Verification System (2013, methodology): “On the other hand, [16] analyzes four different fusion methods.”
Toward an attack-sensitive tamper-resistant biometric recognition with a symmetric matcher: A fingerprint case study (2014, methodology): “Although such an exhaustive combination has also been considered by Marasco et al [5], we further argue the need to categorize the attacks into four groups plus a genuine comparison.”