Performance Improvement Strategies on Template Matching
نویسنده
چکیده
This paper proposes an algorithm for offline recognition of handwritten characters, especially effective for large set characters such as Korean and Chinese characters. The algorithm is based on a template matching method which is easy to implement but suffers from low recognition performance. Two strategies has been developed to improve the performance of the template matching: one is multi-stage preclassification and the other is pairwise reordering. Effectiveness of the algorithm has been proven by an experiment with a handwritten Korean character database named PE92, where 86.0% of recognition accuracy and 15 characters per second of processing speed have been obtained.
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