Benchmarking Fingerprint Minutiae Extractors
| Autor: | Anil K. Jain, Nicholas G. Paulter, Sunpreet S. Arora, Tarang Chugh |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Minutiae
021110 strategic defence & security studies business.industry Computer science Feature extraction 0211 other engineering and technologies 020207 software engineering Pattern recognition 02 engineering and technology Benchmarking Fingerprint recognition ComputingMethodologies_PATTERNRECOGNITION Robustness (computer science) 0202 electrical engineering electronic engineering information engineering Benchmark (computing) Preprocessor NIST Computer vision Artificial intelligence business |
| Zdroj: | BIOSIG |
| DOI: | 10.23919/biosig.2017.8053498 |
| Popis: | The performance of a fingerprint recognition system hinges on the errors introduced in each of its modules: image acquisition, preprocessing, feature extraction, and matching. One of the most critical and fundamental steps in fingerprint recognition is robust and accurate minutiae extraction. Hence we conduct a repeatable and controlled evaluation of one open-source and three commercial-off-the-shelf (COTS) minutiae extractors in terms of their performance in minutiae detection and localization. We also evaluate their robustness against controlled levels of image degradations introduced in the fingerprint images. Experiments were conducted on (i) a total of 3,458 fingerprint images from five public-domain databases, and (ii) 40,000 synthetically generated fingerprint images. The contributions of this study include: (i) a benchmark for minutiae extractors and minutiae interoperability, and (ii) robustness of minutiae extractors against image degradations. |
| Databáze: | OpenAIRE |
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