IDENTITY VERIFICATION ON PARTIAL FINGERPRINT IMAGES USING GLOBAL FEATURE VECTORS
Although there are several commercial applications available in the market, fingerprint identification and verification is still a challenging task in the field of automated computing. Despite the common usage of fingerprint identification systems, current calculation algorithms need to be more developed, since the variations in scanned image significantly effects the success rate. Thus people are frequently requested to re-scan their finger in order to eliminate false-positive verifications. Unquestionably, scanned fingerprints are subject to several external distortions, as is casual scars, regional bruises and partially-blinded scanners. Hence a portion of the local features can not be identified at all. In this study the efficiency of global-image-feature set is tested on partial fingerprint scans. Findings indicate that the success rate of the global feature comparison approach on partial finger print images is %70 higher than that of local feature comparison.
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