Fingerprint classification decreases the number of possible matches in automated fingerprint identification systems by categorizing fingerprints into predefined classes. Support vector machines are widely used in pattern classification and have produced high accuracy when performing fingerprint classification. In order to effectively apply Support vector machines to multi-class fingerprint classification systems.It is proposed a novel method in which the fingerprint classification can be done by the classifier used Naïve Bayes and Support vector machines efficiently reduce the search time by restricting the subsequent searching stage to either left hand thumb and right hand thumb databases.
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