Azmi, Aini Najwa and Nasien, Dewi (2014) Feature vector of binary image using Freeman Chain Code (FCC) representation based on structural classifier. International Journal of Advances in Soft Computing and its Applications, 6 (2). ISSN 2074-8523
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Abstract
This paper presents a recognition system for English Handwritten that utilized Freeman Chain Code (FCC) as data representation. There are 544 features were extracted from character images that used six techniques to extract the features. Before extracting the features, thinning algorithm was applied to the original image to produce a Thinned Binary Image (TBI). A feed forward back propagation neural network was used as classification. National Institute of Standards and Technology (NIST) database are used in the experiment. The accuracy yielded from the system is 87.34%.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | artificial neural network (ANN), feature extraction, freeman chain code (FCC), handwritten character recognition (HCR), thinning algorithm |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Computing |
| ID Code: | 52874 |
| Deposited By: | Siti Nor Hashidah Zakaria |
| Deposited On: | 01 Feb 2016 03:52 |
| Last Modified: | 19 Jul 2018 07:18 |
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