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Performance of Object Classification Using Zernike Moment
Authors:Ariffuddin Joret  Mohammad Faiz Liew Abdullah  Muhammad Suhaimi Sulong  Asmarashid Ponniran  Siti Zuraidah Zainudin
Affiliation:1.Faculty of Electrical and Electronic Engineering,Universiti Tun Hussein Onn Malaysia,86400 Parit Raja,Johor,Malaysia
Abstract:Moments have been used in all sorts of object classification systems based on image. There are lots of moments studied by many researchers in the area of object classification and one of the most preference moments is the Zernike moment. In this paper, the performance of object classification using the Zernike moment has been explored. The classifier based on neural networks has been used in this study. The results indicate the best performance in identifying the aggregate is at 91.4% with a ten orders of the Zernike moment. This encouraging result has shown that the Zernike moment is a suitable moment to be used as a feature of object classification systems.
Keywords:Features extraction   neural network   object classification   Zernike moment
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