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

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. Journal of Electrical and Electronic Systems Research (JEESR), 9 (1): 8. pp. 43-51. ISSN 1985-5389

Abstract

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.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Mustafa Kamal, N. D.
diyanahmustaffa@yahoo.com
Jalil, N.
UNSPECIFIED
Hashim, H.
UNSPECIFIED
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electronics > Pattern recognition systems
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Electrical Engineering
Journal or Publication Title: Journal of Electrical and Electronic Systems Research (JEESR)
UiTM Journal Collections: UiTM Journals > Journal of Electrical and Electronic Systems Research (JEESR)
ISSN: 1985-5389
Volume: 9
Number: 1
Page Range: pp. 43-51
Keywords: Back propagation neural network, discrete wavelet transform, fastener recognition, RGB colour features, shape-based features, ten-fold cross validation, Zernike moments
Date: December 2016
URI: https://ir.uitm.edu.my/id/eprint/63005
Edit Item
Edit Item

Download

[thumbnail of 63005.pdf] Text
63005.pdf

Download (846kB)

ID Number

63005

Indexing

Statistic

Statistic details