Please use this identifier to cite or link to this item: http://148.72.244.84/xmlui/handle/xmlui/9043
Title: Improving Handwritten Isolated Arabic characters Recognition with Particle Swarm Optimization Algorithm
Authors: Majida Ali Abed
Keywords: Pattern recognition techniques, handwritten characters, Recognition, Feature extraction, particles swarm optimization, Algorithm.
Issue Date: 2014
Publisher: university of Diyala
Abstract: This manuscript considers a new approach to Simplifying pattern recognition based on simulation of behavior of schools of fish and flocks of birds and called particles swarm optimization algorithm (PSOA). We present an overview of the proposed approaches to be optimized and tested on a number of handwritten characters in the experiments as well. Experimental results of the optimization algorithm are found to be very efficient and give higher recognition accuracy. It is noted that the PSOA in general generates an optimized comparison between the input samples and database samples which improves the final recognition rate. Experimental results show that the PSOA algorithm is convergence and more accurate in solution with low error recognition rate .The recognition rate of our proposed system is 87.856% and rate error recognition is 12.142%.
URI: http://148.72.244.84:8080/xmlui/handle/xmlui/9043
ISSN: 2222-8373
Appears in Collections:مجلة ديالى للعلوم الاكاديمية / Academic Science Journal (Acad. Sci. J.)

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