Feature Extractor for the Classification of Approved Halal Logo in Malaysia /

Khairul Muzzammil Saipullah

Feature Extractor for the Classification of Approved Halal Logo in Malaysia / Khairul Muzzammil Saipullah, Nurul Atiqah Ismail and Yewguan Soo - New Jersey : The Institute of Electrical and Electronics Engineers 2012

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.

9781467331432


Feature Extractor
Fourier Principle Magnitude,
Logo classification
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