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CLC number: TP391.4
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 0000-00-00
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An approach to offline handwritten Chinese character recognition based on segment evaluation of adaptive duration
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LI Guo-hong, SHI Peng-fei. An approach to offline handwritten Chinese character recognition based on segment evaluation of adaptive duration[J]. Journal of Zhejiang University Science A, 2004, 5(11): 1392-1397.
@article{title="An approach to offline handwritten Chinese character recognition based on segment evaluation of adaptive duration",
author="LI Guo-hong, SHI Peng-fei",
journal="Journal of Zhejiang University Science A",
volume="5",
number="11",
pages="1392-1397",
year="2004",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.2004.1392"
}
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%A SHI Peng-fei
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%DOI 10.1631/jzus.2004.1392
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T1 - An approach to offline handwritten Chinese character recognition based on segment evaluation of adaptive duration
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A1 - SHI Peng-fei
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SP - 1392
EP - 1397
%@ 1869-1951
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.2004.1392
Abstract: This paper presents a methodology for off-line handwritten Chinese character recognition based on mergence of consecutive segments of adaptive duration. The handwritten Chinese character string is partitioned into a sequence of consecutive segments, which are combined to implement dissimilarity evaluation within a sliding window whose durations are determined adaptively by the integration of shapes and context of evaluations. The average stroke width is estimated for the handwritten Chinese character string, and a set of candidate character segmentation boundaries is found by using the integration of pixel and stroke features. The final decisions on segmentation and recognition are made under minimal arithmetical mean dissimilarities. Experiments proved that the proposed approach of adaptive duration outperforms the method of fixed duration, and is very effective for the recognition of overlapped, broken, touched, loosely configured Chinese characters.
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