The analysis of shape-based, DWT and zernike moments feature extraction techniques for fasterner recognition using 10-fold cross validation multilayer perceptrons / N. D. Mustaffa Kamal, N. Jalil and H. Hashim
This paper presents an analysis of three feature extraction techniques which are the shape-based, Zernike moments and Discrete Wavelet Transform for fastener recognition. RGB colour features are also added to these major feature extractors to enhance the classification result. The classifier used in...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | en |
| Published: |
UiTM Press
2016
|
| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/63005/1/63005.pdf https://ir.uitm.edu.my/id/eprint/63005/ https://jeesr.uitm.edu.my/v1/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1839753627298693120 |
|---|---|
| author | Mustafa Kamal, N. D. Jalil, N. Hashim, H. |
| author_facet | Mustafa Kamal, N. D. Jalil, N. Hashim, H. |
| author_sort | Mustafa Kamal, N. D. |
| building | Tun Abdul Razak Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Mara |
| content_source | UiTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | This paper presents an analysis of three feature extraction techniques which are the shape-based, Zernike moments and Discrete Wavelet Transform for fastener recognition. RGB colour features are also added to these major feature extractors to enhance the classification result. The classifier used in this experiment is back propagation neural network and the result in general is strengthen using ten-fold cross validation. The result is measured using percentage accuracy and Kappa statistics. The overall results showed that the best feature extraction techniques are Zernike moment group 3 and DWT both with added colour features. |
| format | Article |
| id | my.uitm.ir-63005 |
| institution | Universiti Teknologi Mara |
| language | en |
| publishDate | 2016 |
| publisher | UiTM Press |
| record_format | eprints |
| spelling | my.uitm.ir-630052025-08-05T05:02:19Z https://ir.uitm.edu.my/id/eprint/63005/ The analysis of shape-based, DWT and zernike moments feature extraction techniques for fasterner recognition using 10-fold cross validation multilayer perceptrons / N. D. Mustaffa Kamal, N. Jalil and H. Hashim jeesr Mustafa Kamal, N. D. Jalil, N. Hashim, H. Pattern recognition systems This paper presents an analysis of three feature extraction techniques which are the shape-based, Zernike moments and Discrete Wavelet Transform for fastener recognition. RGB colour features are also added to these major feature extractors to enhance the classification result. The classifier used in this experiment is back propagation neural network and the result in general is strengthen using ten-fold cross validation. The result is measured using percentage accuracy and Kappa statistics. The overall results showed that the best feature extraction techniques are Zernike moment group 3 and DWT both with added colour features. UiTM Press 2016-12 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/63005/1/63005.pdf Mustafa Kamal, N. D. and Jalil, N. and Hashim, H. (2016) The analysis of shape-based, DWT and zernike moments feature extraction techniques for fasterner recognition using 10-fold cross validation multilayer perceptrons / N. D. Mustaffa Kamal, N. Jalil and H. Hashim. (2016) Journal of Electrical and Electronic Systems Research (JEESR) <https://ir.uitm.edu.my/view/publication/Journal_of_Electrical_and_Electronic_Systems_Research_=28JEESR=29.html>, 9 (1): 8. pp. 43-51. ISSN 1985-5389 https://jeesr.uitm.edu.my/v1/ |
| spellingShingle | Pattern recognition systems Mustafa Kamal, N. D. Jalil, N. Hashim, H. The analysis of shape-based, DWT and zernike moments feature extraction techniques for fasterner recognition using 10-fold cross validation multilayer perceptrons / N. D. Mustaffa Kamal, N. Jalil and H. Hashim |
| title | The analysis of shape-based, DWT and zernike moments feature extraction techniques for fasterner recognition using 10-fold cross validation multilayer perceptrons / N. D. Mustaffa Kamal, N. Jalil and H. Hashim |
| title_full | The analysis of shape-based, DWT and zernike moments feature extraction techniques for fasterner recognition using 10-fold cross validation multilayer perceptrons / N. D. Mustaffa Kamal, N. Jalil and H. Hashim |
| title_fullStr | The analysis of shape-based, DWT and zernike moments feature extraction techniques for fasterner recognition using 10-fold cross validation multilayer perceptrons / N. D. Mustaffa Kamal, N. Jalil and H. Hashim |
| title_full_unstemmed | The analysis of shape-based, DWT and zernike moments feature extraction techniques for fasterner recognition using 10-fold cross validation multilayer perceptrons / N. D. Mustaffa Kamal, N. Jalil and H. Hashim |
| title_short | The analysis of shape-based, DWT and zernike moments feature extraction techniques for fasterner recognition using 10-fold cross validation multilayer perceptrons / N. D. Mustaffa Kamal, N. Jalil and H. Hashim |
| title_sort | analysis of shape-based, dwt and zernike moments feature extraction techniques for fasterner recognition using 10-fold cross validation multilayer perceptrons / n. d. mustaffa kamal, n. jalil and h. hashim |
| topic | Pattern recognition systems |
| url | https://ir.uitm.edu.my/id/eprint/63005/1/63005.pdf https://ir.uitm.edu.my/id/eprint/63005/ https://jeesr.uitm.edu.my/v1/ |
| url_provider | http://ir.uitm.edu.my/ |