On Fingerprint Identification
Fatima Wang
Corresponding
ETH Zurich
Ming Jayawardena
University of California, Berkeley
Abstract
Rapid industrial growth in South Asia has intensified the demand for a better quantitative understanding of fingerprint identification. Sample specimens were prepared and tested, and the resulting data analysed by fuzzy logic control. The measured and predicted values of fingerprint identification differed by no more than a few per cent. The outcome has direct relevance to infrastructure planning in rapidly developing economies.
Keywords:
fingerprint identificationfuzzy logic controlartificial neural networkrainfall-runoff
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