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Scientific Transactions in Environment and Technovation

Research

Scientific Transactions in Environment and Technovation, | 0
Year : 2016 | Volume: 9 | Issue: 3 | Pages : 144-148

Hive tool instead of customary Etl in big data

Abstract :

Fingerprint Classification provides an important indexing mechanism in a fingerprint database. An accurate and consistent classification can greatly reduce fingerprint matching time for a large database. We present a fingerprint classification algorithm which is able to achieve accuracy better than previously reported in the literature. We classify fingerprints into seven categories: plain arch, tented arch, left loop, right loop, plain whorl, central pocket whorl and double loop whorl. The least square orientation estimation algorithm uses a novel representation to make a classification It has been tested on 4,000 images in the NIST-4 database. For the seven-class problem a classification accuracy of 95.08 percent is achieved. For the five-class problem (whorl, right loop, left loop, arch and tented arch) we are able to achieve a classification accuracy of 97 percent.

Keywords:

fingerprint classification,least square Orientation.

Citation: *,

( 2016), Hive tool instead of customary Etl in big data. Scientific Transactions in Environment and Technovation, 9(3): 144-148

Mr.Veerapathiran K

Correspondence: S.Bhuvana


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