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Performance of Object Classification Using Zernike Moment
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作者 ariffuddin joret Mohammad Faiz Liew Abdullah +2 位作者 Muhammad Suhaimi Sulong Asmarashid Ponniran Siti Zuraidah Zainudin 《Journal of Electronic Science and Technology》 CAS 2014年第1期90-94,共5页
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... 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. 展开更多
关键词 Features extraction neural network object classification Zernike moment.
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