Haron, Habibollah and Yuhaniz, Siti Sophiayati and D., Nasien (2010) Support Vector Machine (SVM) for english handwritten character recognition. In: 2010 2nd International Conference on Computer Engineering and Applications, ICCEA 2010, 2010, Bali Island, Indonesia.
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Official URL: http://dx.doi.org/10.1109/ICCEA.2010.56
This paper proposes a recognition model for English handwritten (lowercase, uppercase and letter) character recognition that uses Freeman chain code (FCC) as the representation technique of an image character. Chain code representation gives the boundary of a character image in which the codes represent the direction of where is the location of the next pixel. An FCC method that uses 8-neighbourhood that starts from direction labelled as 1 to 8 is used. Randomized algorithm is used to generate the FCC. After that, features vector is built. The criteria of features to input the classification is the chain code that converted to 64 features. Support vector machine (SVM) is chosen for the classification step. NIST Databases are used as the data in the experiment. Our test results show that by applying the proposed model, we reached a relatively high accuracy for the problem of English handwritten recognition.
|Item Type:||Conference or Workshop Item (Paper)|
|Uncontrolled Keywords:||Freeman chain code (FCC), heuristic method, Support vector machine (SVM), features vector, randomized algorithm|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Divisions:||Computer Science and Information System (Formerly known)|
|Deposited By:||Liza Porijo|
|Deposited On:||30 Aug 2012 04:18|
|Last Modified:||05 Feb 2017 08:13|
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