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- W36998262 abstract "Automated fingerprint identification systems (AFIS) are based on techniques to identify an unknown fingerprint with those present in the database. These techniques can be either localized (generally minutiae-based) or globalized (generally transform-based). The current day applications have to deal with large databases and fast processing and hence new techniques with less processing time need to be developed. In this paper we develop a new technique for fingerprint identification which reduces the processing time considerably as compared to standard existing techniques. This techniques is in the frequency domain where coefficients (feature vectors) are generated using Walsh transform. Sectionization techniques are used to reduce the number of feature vectors. Proposed method is evaluated on standard database. The experimental results show that this algorithm could correctly identify fingerprints with accuracy more than 93% in case of larger number of sectors." @default.
- W36998262 created "2016-06-24" @default.
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- W36998262 date "2011-01-01" @default.
- W36998262 modified "2023-09-25" @default.
- W36998262 title "Fingerprint Identification Using Sectionized Walsh Transform of Row and Column Mean" @default.
- W36998262 cites W2127083748 @default.
- W36998262 doi "https://doi.org/10.1007/978-3-642-18440-6_67" @default.
- W36998262 hasPublicationYear "2011" @default.
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