Feature Extractor for the Classification of Approved Halal Logo in Malaysia

Saipullah, Khairul Muzzammil (2012) Feature Extractor for the Classification of Approved Halal Logo in Malaysia. In: IEEE International Conference on Control System, Computing and Engineering, 23-25 November 2012, Penang .

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Abstract

This paper present a new feature extractors called the Fractionalized Principle Magnitude (FPM) that is evaluated in the classification of approved Halal logo with respect to classification accuracy and time consumptions. Feature can be classified into two group; global feature and local feature. In this study, several feature extractors have been compared with the proposed method such as histogram of gradient (HOG), Hu moment, Zernike moment and wavelet co-occurrence histogram (WCH). The experiments are conducted on 50 different approved Halal logos. The result shows that proposed FPM method achieves the highest accuracy with 90.4% whereas HOG, Zernike moment, WCH and Hu moment achieve 75.2%, 64.4%, 47.2% 44.4% of accuracies, respectively.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Electronics and Computer Engineering > Department of Computer Engineering
Depositing User:	Engr. Khairul Muzzammil Saipullah
Date Deposited:	15 Jul 2013 03:56
Last Modified:	28 May 2015 03:57
URI:	http://eprints.utem.edu.my/id/eprint/8550
Statistic Details:	View Download Statistic

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