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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/dspace/handle/123456789/7162

Title: Trademarks cassification by Moment Invariant and FuzzyARTMAP
Authors: Shahrul Nizam, Yaakob
Puteh, Saad
Abu Hassan, Abdullah
Keywords: Fuzzy ARTMAP;Geometric moment;Zernike moment;Trademarks;Optical pattern recognition;Image processing
Issue Date: 14-May-2005
Publisher: Kolej Universiti Kejuruteraan Utara Malaysia
Citation: p.117-122
Series/Report no.: Proceedings of the 1st International Workshop on Artificial Life and Robotics
Abstract: The purpose of automated image classification is to facilitate a machine to classify image patterns without human intervention. There are a variety of approaches proposed to perform the task. In our case, the image chosen is that of trademark. Geometric and Zernike Moment techniques are employed to extract a set of patterns in terms of feature vectors from the image. Fuzzy ARTMAP is then utilized to classify the image patterns. In order to test the invariant properties of the feature vectors, trademark images are manipulated into various orientations in the aspect of rotational, translational and size. The classification performance of Fuzzy ARTMAP is evaluated based on cross validation techniques. It is found that Zernike Moments displayed a higher classification accuracy when compared to Geometric Moments.
Description: Organized by Kolej Universiti kejuruteraan Utara Malaysia (KUKUM), 14th - 15th May 2005 at Putra Palace Hotel, Kangar, Perlis.
URI: http://hdl.handle.net/123456789/7162
Appears in Collections:Conference Papers

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