A novel palmprint segmentation technique
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Date
2011-12-12
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Abstract
Recent 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.
Description
Keywords
Transient Multiexponential, Data Selection, Cramer Rao, Lower Bound
Citation
Rotinwa-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.