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Java Characters Recognition using Evolutionary Neural Network and Combination of Chi2 and Backpropagation Neural Network

Adipranata, Rudy (2014) Java Characters Recognition using Evolutionary Neural Network and Combination of Chi2 and Backpropagation Neural Network. International Journal of Applied Engineering Research, 9 (22). pp. 15395-15406. ISSN 0973-4562

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        Abstract

        Javanese language is the language used by the people on the island of Java and it has its own form of letters called Java characters. Recognition of Java characters is quite difficult because it consist of basic characters, numbers, complementary characters, and so on. In this research we developed a system to recognize Java characters and compared two methods of neural network namely evolutionary neural network and combination of Chi2 and backpropagation neural network. Input for the system is a digital image of Java characters. Before entering into the neural network, the digital image is processed by reducing noise, segmentation and thinning and feature extraction. From experimental result, evolutionary neural network has 60 average recognition accuracy, while combination of Chi2 and backpropagation network has 70 average recognition accuracy

        Item Type: Article
        Uncontrolled Keywords: Java characters recognition, Evolutionary neural network, Backpropagation neural network, Chi2
        Subjects: Q Science > QA Mathematics > QA76 Computer software
        Divisions: Faculty of Industrial Technology > Informatics Engineering Department
        Depositing User: Admin
        Date Deposited: 29 Nov 2014 02:03
        Last Modified: 23 May 2018 08:23
        URI: http://repository.petra.ac.id/id/eprint/16813

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