A novel palmprint segmentation technique

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dc.contributor.authorRotinwa-Akinbile, M. O.
dc.contributor.authorAibinu, A. M.
dc.contributor.authorSalami, Momoh-Jimoh E.
dc.date.accessioned2019-11-04T11:50:19Z
dc.date.available2019-11-04T11:50:19Z
dc.date.issued2011-12-12
dc.description.abstractRecent paradigm shift from the conventional contact based palmprint recognition to contactless based systems (CBS) has necessitated the development of a variety of these systems. A major challenge of these systems is it robustness to illumination variation in unconstrained environment, thus making segmentation difficult. In this paper, the acquired image undergoes color space conversion and the output is filtered using coefficients obtained from the training of an artificial neural network (ANN) based model coefficient determination technique. Performance analysis of the proposed technique shows better performance in term of mean square error, true positive rate and accuracy when compared with two other techniques. Furthermore, it has also been observed that the proposed method is illumination invariant hence its suitability for deployment in contactless palmprint recognition systems.en_US
dc.identifier.citationRotinwa-Akinbile, M. O., Aibinu, A. M., & Salami, M. J. E. (2011, December). A novel palmprint segmentation technique. In 2011 First International Conference on Informatics and Computational Intelligence (pp. 235-239). IEEE.en_US
dc.identifier.uri10.1109/ICI.2011.45
dc.identifier.urihttp://repository.elizadeuniversity.edu.ng/handle/20.500.12398/618
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectTransient Multiexponentialen_US
dc.subjectData Selectionen_US
dc.subjectCramer Raoen_US
dc.subjectLower Bounden_US
dc.titleA novel palmprint segmentation techniqueen_US
dc.typeArticleen_US
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