Fifteenth- to Eighteenth-Century European Paintings in the by Charles; et. al. Sterling

By Charles; et. al. Sterling

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MCS 2007. LNCS, vol. 4472, pp. 344–356. Springer, Heidelberg (2007) Definition of Fingerprint Scanner Image Quality Specifications by Operational Quality A. Alessandroni1, R. Cappelli2, M. Ferrara2, and D. it Abstract. This paper analyzes two recently released image quality specifications for single-finger scanners and proposes three new specifications targeted to different types of applications. A comparison of the potential effects on fingerprint recognition accuracy of the various specifications is carried out using an approach based on the definition of “operational quality”.

Improving classification with class-independent quality measures: Q-stack in face verification. Z. ) ICB 2007. LNCS, vol. 4642. Springer, Heidelberg (2007) 4. : Q-stack: uni- and multimodal classifier stacking with quality measures. In: Proc. 7th Intl. Workshop on Multiple Classifier Systems, Prague, Czech Republic (May 2007) 5. S. VISIT program. In: Proc. National Academy of Sciences (2005) 6. : Quality-based score level fusion in multibiometric systems. In: Proc. International Conference on Pattern Recognition, Hong Kong, China, vol.

1, it is useful to compare the five IQS as shown in Table 3, where the “strictness” of the various quality parameters with respect to the FBI IAFIS IQS [3] is highlighted. The most “tolerant” specification is CNIPA-C, which has the least demanding requirements for all the parameters: as it was reasonable to expect, this specification can cause the largest performance drop (182% on the average). Less tolerant but still not very strict are PIV and CNIPA-B (both with three “L” and three “M” requirements); however the loss of performance that can be caused by them is definitely different: on the average 156% and 44%, respectively.

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