Optimal correlation filter for fingerprint verification
| Autor: | Colin Soutar, Danny Roberge, Bhagavatula Vijaya Kumar |
|---|---|
| Rok vydání: | 1998 |
| Předmět: |
Computer science
business.industry Fingerprint (computing) Fingerprint Verification Competition Pattern recognition Fingerprint recognition computer.software_genre Adaptive filter Filter design Filter (video) Distortion Kernel adaptive filter Artificial intelligence Data mining business computer Root-raised-cosine filter |
| Zdroj: | Optical Pattern Recognition IX. |
| ISSN: | 0277-786X |
| DOI: | 10.1117/12.304756 |
| Popis: | We present the derivation of an optimal correlation filter for fingerprint verification. The filter comprises multiple versions of the system user's fingerprint (i.e. it is a composite filter). Also, the characteristics of the filter can be adjusted so that its performance in a correlator is similar to that of a matched-filter or an inverse-filter, or some compromise between the two. It is these attributes that make this filter structure attractive for the task of fingerprint verification. The composite nature of the filter offers distortion tolerance by encompassing several different versions of the fingerprint image, while the tailored characteristics of the filters allows us to produce output correlation planes that can easily be processed. The filter was developed using a 'standard' database, with the objective of separating the two classes of input to the system: 'legitimate users' and 'attackers.' Specifically, the filter is optimized to minimize the probability of error (i.e. misclassification of user). Both the design and the implementation of the optimal fingerprint filter are covered in this paper. |
| Databáze: | OpenAIRE |
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