Hand geometry recognition: an approach for closed and separated fingers

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dc.contributor.authorAdeniyi, J. K.
dc.contributor.authorOladele, Tinuke Omolewa
dc.contributor.authorAkande, O. N.
dc.contributor.authorAdeniyi, T. T.
dc.date.accessioned2023-05-12T12:42:31Z
dc.date.available2023-05-12T12:42:31Z
dc.date.issued2022
dc.description.abstractHand geometry has been a biometric trait that has attracted attention from several researchers. This stems from the fact that it is less intrusive and could be captured without contact with the acquisition device. Its application ranges from forensic examination to basic authentication use. However, restrictions in hand placement have proven to be one of its challenges. Users are either instructed to keep their fingers separate or closed during capture. Hence, this paper presents an approach to hand geometry using finger measurements that considers both closed and separate fingers. The system starts by cropping out the finger section of the hand and then resizing the cropped fingers. 20 distances were extracted from each finger in both separate and closed finger images. A comparison was made between Manhattan distance and Euclidean distance for features extraction. The support vector machine (SVM) was used for classification. The result showed a better result for Euclidean distance with a false acceptance ratio (FAR) of 0.6 and a false rejection ratio (FRR) of 1.2.en_US
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/20.500.12484/10171
dc.language.isoenen_US
dc.publisherInternational Journal of Electrical and Computer Engineering (IJECE)en_US
dc.subjectBiometrics, Euclidean distance, Hand geometry, Manhattan distance, Support vector machineen_US
dc.titleHand geometry recognition: an approach for closed and separated fingersen_US
dc.typeArticleen_US

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