Palmprint recognition using principle component analysis implemented on TMS320C6713 DSP processor
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Universiti Teknikal Malaysia Melaka
2019
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my.unimap-635642019-12-03T04:33:25Z Palmprint recognition using principle component analysis implemented on TMS320C6713 DSP processor Thulfiqar Hussein, Mandeel Muhammad Imran, Ahmad Mohd Nazrin, Md Isa Ruzelita, Ngadiran m.imran@unimap.edu.my Biometrics Palmprint recognition Principal component analysis Feature extraction Link to publisher's homepage at http://journal.utem.edu.my This paper presents a human identification system using eigen-palm images. The proposed method consists of three main stages. The preprocessing stage computes the palmprint images to capture important information and produce a better representation of palmprint image data. The second stage extracts significant features from palmprint images and reduces the dimension of the palmprint image data by applying the principal component analysis (PCA) technique. Low-dimensional features in the feature space are assumed to be Gaussian. Thus, the Euclidean distance classifier can be used in the matching process to compare test image with the template. The proposed method is tested using a benchmark PolyU dataset. Experimental results show that the best achieved recognition rate is 97.5% when the palmprint image is represented using 34 PCA coefficients. Moreover, the Euclidean distance classifier is implemented on a digital signal processor (DSP) board. Implementing the proposed algorithm using the DSP processor achieves better performance in computation time compared with a personal computer-based system 2019-12-03T04:33:25Z 2019-12-03T04:33:25Z 2016 Article Link to publisher's homepage at http://journal.utem.edu.my, vol.8(4), 2016, 41-46. 2180–1843 2289-8131 (online) http://dspace.unimap.edu.my:80/xmlui/handle/123456789/63564 journal.utem.edu.my/index.php/jtec/article/view/1169 en Universiti Teknikal Malaysia Melaka |
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Universiti Malaysia Perlis |
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| language |
English |
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Biometrics Palmprint recognition Principal component analysis Feature extraction |
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Biometrics Palmprint recognition Principal component analysis Feature extraction Thulfiqar Hussein, Mandeel Muhammad Imran, Ahmad Mohd Nazrin, Md Isa Ruzelita, Ngadiran Palmprint recognition using principle component analysis implemented on TMS320C6713 DSP processor |
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Link to publisher's homepage at http://journal.utem.edu.my |
| author2 |
m.imran@unimap.edu.my |
| author_facet |
m.imran@unimap.edu.my Thulfiqar Hussein, Mandeel Muhammad Imran, Ahmad Mohd Nazrin, Md Isa Ruzelita, Ngadiran |
| format |
Article |
| author |
Thulfiqar Hussein, Mandeel Muhammad Imran, Ahmad Mohd Nazrin, Md Isa Ruzelita, Ngadiran |
| author_sort |
Thulfiqar Hussein, Mandeel |
| title |
Palmprint recognition using principle component analysis implemented on TMS320C6713 DSP processor |
| title_short |
Palmprint recognition using principle component analysis implemented on TMS320C6713 DSP processor |
| title_full |
Palmprint recognition using principle component analysis implemented on TMS320C6713 DSP processor |
| title_fullStr |
Palmprint recognition using principle component analysis implemented on TMS320C6713 DSP processor |
| title_full_unstemmed |
Palmprint recognition using principle component analysis implemented on TMS320C6713 DSP processor |
| title_sort |
palmprint recognition using principle component analysis implemented on tms320c6713 dsp processor |
| publisher |
Universiti Teknikal Malaysia Melaka |
| publishDate |
2019 |
| url |
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/63564 |
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1654961443310665728 |