Palmprint identification using invariant moments algorithm based on wavelet transform

Inass Shahadha Hussein, Md. Jan Nordin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Because of the uniqueness of palmprints found on the palms of humans, palmprint identification has been used in several applications. It is usually associated with criminal identification, and has now become more popular in civilian applications. Therefore, the aim of the proposed model is to improve personal identification based on extracting shape feature using moments algorithm based on wavelet transform and matching algorithm, which is proposed in this model. This model has shown promising results without affecting rotation, translation and scaling of objects, because it is associated with the use of a good description of shape features. This system has been tested using databases from the Chinese Academy of Sciences (CASIA), in Beijing. By using false rejection rate (FRR) and false acceptance rate (FAR), we calculated the accuracy of identification. The experiment shows 98 % identification rate in the CASIA database.

Original languageEnglish
Title of host publicationLecture Notes in Electrical Engineering
PublisherSpringer Verlag
Pages905-914
Number of pages10
Volume315
ISBN (Print)9783319076737
DOIs
Publication statusPublished - 2015
Event1st International Conference on Communication and Computer Engineering, ICOCOE 2014 - Malacca
Duration: 20 May 201421 May 2014

Publication series

NameLecture Notes in Electrical Engineering
Volume315
ISSN (Print)18761100
ISSN (Electronic)18761119

Other

Other1st International Conference on Communication and Computer Engineering, ICOCOE 2014
CityMalacca
Period20/5/1421/5/14

Fingerprint

Wavelet transforms
Identification (control systems)
Experiments

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

Cite this

Hussein, I. S., & Nordin, M. J. (2015). Palmprint identification using invariant moments algorithm based on wavelet transform. In Lecture Notes in Electrical Engineering (Vol. 315, pp. 905-914). (Lecture Notes in Electrical Engineering; Vol. 315). Springer Verlag. https://doi.org/10.1007/978-3-319-07674-4_85

Palmprint identification using invariant moments algorithm based on wavelet transform. / Hussein, Inass Shahadha; Nordin, Md. Jan.

Lecture Notes in Electrical Engineering. Vol. 315 Springer Verlag, 2015. p. 905-914 (Lecture Notes in Electrical Engineering; Vol. 315).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Hussein, IS & Nordin, MJ 2015, Palmprint identification using invariant moments algorithm based on wavelet transform. in Lecture Notes in Electrical Engineering. vol. 315, Lecture Notes in Electrical Engineering, vol. 315, Springer Verlag, pp. 905-914, 1st International Conference on Communication and Computer Engineering, ICOCOE 2014, Malacca, 20/5/14. https://doi.org/10.1007/978-3-319-07674-4_85
Hussein IS, Nordin MJ. Palmprint identification using invariant moments algorithm based on wavelet transform. In Lecture Notes in Electrical Engineering. Vol. 315. Springer Verlag. 2015. p. 905-914. (Lecture Notes in Electrical Engineering). https://doi.org/10.1007/978-3-319-07674-4_85
Hussein, Inass Shahadha ; Nordin, Md. Jan. / Palmprint identification using invariant moments algorithm based on wavelet transform. Lecture Notes in Electrical Engineering. Vol. 315 Springer Verlag, 2015. pp. 905-914 (Lecture Notes in Electrical Engineering).
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