Abstract
Abstract In this paper, a new algorithm for fingerprint recognition is presented. It is called the Histogram-Partitioning, Median-Filtering Fingerprint Recognition Algorithm (HMFA). The performance of the algorithm is tested through ensemble averaging of the mean square error. It is applied on different fingerprints having various backgrounds, resolutions and dimensions. Initially, a database is formed using several fingerprints. Those are subjected to various types of noise, such as impulsive and Gaussian noises. Then HMFA is applied to filter the noise. Next, using the query designed for the algorithm, the fingerprint recognition from the database is done. This is accomplished by selecting the fingerprint from the database that produces the least mean square error in comparison to the fingerprint in question. The assessment is made using ensemble averaging.
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