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An Efficient Feature Extraction and Dimensionality Reduction Scheme for Isolated Greek Handwritten Character Recognition
Curitiba, Parana, Brazil September 23-September 26
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDAR.2007.49Ninth International Conference on Doc ...
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G. Vamvakas, National Center for Scientific Research "Demokritos", GR-153 10 Agia Paraskevi, Athens, Greece
B. Gatos, National Center for Scientific Research "Demokritos", GR-153 10 Agia Paraskevi, Athens, Greece
S. Petridis, National Center for Scientific Research "Demokritos", GR-153 10 Agia Paraskevi, Athens, Greece
N. Stamatopoulos, National Center for Scientific Research "Demokritos", GR-153 10 Agia Paraskevi, Athens, Greece
In this paper, we present an off-line methodology for isolated Greek handwritten character recognition based on efficient feature extraction followed by a suitable feature vector dimensionality reduction scheme. Extracted features are based on (i) horizontal and vertical zones, (ii) the projections of the character profiles, (iii) distances from the character boundaries and (iv) profiles from the character edges. The combination of these types of features leads to a 325- dimensional feature vector. At a next step, a dimensionality reduction technique is applied, according to which the dimension of the feature space is lowered down to comprise only the features pertinent to the discrimination of characters into the given set of letters. In this paper, we also present a new Greek handwritten database of 36,960 characters that we created in order to measure the performance of the proposed methodology.
Citation:
G. Vamvakas, B. Gatos, S. Petridis, N. Stamatopoulos, "An Efficient Feature Extraction and Dimensionality Reduction Scheme for Isolated Greek Handwritten Character Recognition," icdar, vol. 2, pp.1073-1077, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 2, 2007
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