MCYT baseline corpus: a bimodal biometric database

By Javier Ortega-Garcia, Julian Fierrez, D. Simon, J. González, Marcos Faúndez-Zanuy, V. Espinosa, A. Satué, I. Hernáez, J. J. Igarza, C. Vivaracho and 2 more. 2003

762 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/b069e125442995787119db3bfa71dff5d965f3aa

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Citations in the corpus

Automatic Signature Verification: The State of the Art (2008, background): “the same time and to allow very natural writing since an almost standard pen and paper are used [106], [239].”
SDUMLA-HMT: A Multimodal Biometric Database (2011, background): “BANCA [6] and XM2VTS [7] include face and voice; MYCT [8] includes fingerprint and signature.”
An Off-line Signature Verification System Based on Fusion of Local and Global Information (2004, methodology): “A subcorpus of the larger MCYT bimodal database [26] is used for the experiments.”
An evaluation of indirect attacks and countermeasures in fingerprint verification systems (2011, methodology): “The hill climbing attacks have been studied using a subcorpus of the MCYT database (Ortega-Garcia and Fierrez-Aguilar, 2003).”
Learning features for offline handwritten signature verification using deep convolutional neural networks (2017, methodology): “We conducted experiments using the datasets GPDS-960 [9], MCYT-75 [34], CEDAR [35] and the Brazilian PUC-PR [36].”
HMM-based on-line signature verification: Feature extraction and signature modeling (2007, methodology): “The initial configuration for the experiments is as follows (Ortega-Garcia et al., 2003a): 4 HMM states, 8 mixtures per state and 5 training signatures from different sessions.”
Multimodal fusion for multimedia analysis: a survey (2010, background): “tains synchronized video and speech data; BIOMET [42] that contains face, speech, fingerprint, hand and signature modalities; MYCT [93] that contains 10-print fingerprint”
Performance of Biometric Quality Measures (2007, methodology): “[6] reviewed five algorithms and used the fingerprints of the multimodal MCYT corpus [7] to compare the distributions of the algorithms’ quality assignments with the result that most of the algorithms behave similarly.”