Comparative Analysis of Fingerprint Classification Algorithms- A review
DOI:
https://doi.org/10.26438/ijcse/v6i5.728734Keywords:
Fingerprint Classification, statistical classifiers, rule-based classifiers, neural networks, structural classifiers, hybrid classifiersAbstract
Fingerprint classification plays an important role in automatic recognition of fingerprints from a given dataset. It significantly reduces the time taken to map a fingerprint to its nearest match by providing a broad classification of given fingerprint into its relevant class and performing the further search in that class domain only. Various rule-based, model-based and structure-based approaches have been proposed and used to perform such classification. This paper discusses the various mechanism employed to categorize fingerprints into basic classes like arch, whorl, left loop, right loop and tented arch along with the advantages and limitations of each approach. The paper aims to provide a concise study and performance based comparison of various fingerprint classification approaches and the different techniques they use to perform the classification.
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