New matching methods for dissimilar handwritten character images
Identifieur interne : 002416 ( Main/Merge ); précédent : 002415; suivant : 002417New matching methods for dissimilar handwritten character images
Auteurs : X. Zhu [République populaire de Chine] ; Y. Su [République populaire de Chine] ; S. Wang [République populaire de Chine] ; C. Georger [France]Source :
- SPIE proceedings series [ 1017-2653 ] ; 1998.
Descripteurs français
- Pascal (Inist)
English descriptors
- KwdEn :
Abstract
New approaches to the problem of matching method for dissimilar handwritten character images are presented in this paper. One of them is for the offline recognition of dissimilar two-stroke digits which are difficult to discriminate. Several measures are taken to obtain proper division and description of the two strokes to further discrimination. In the recognition stage we combined syntactic analysis with statistical calculation. The other approach is for verifying offline handwritten Chinese signatures. Local connection properties are fully employed and the weighted distances are calculated on the whole signature image. Experiments results show that using the proposed matching methods increased the recognition rate and improved the reliability of our OCR system and is also helpful for verification of handwritten Chinese signatures. Pattern recognition, matching, handwritten character image, variation, measure, signature verification.
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Pascal:99-0196386Le document en format XML
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<term>Reconnaissance forme</term>
<term>Traitement image</term>
<term>Concordance forme</term>
<term>Caractère manuscrit</term>
<term>Chinois</term>
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<front><div type="abstract" xml:lang="en">New approaches to the problem of matching method for dissimilar handwritten character images are presented in this paper. One of them is for the offline recognition of dissimilar two-stroke digits which are difficult to discriminate. Several measures are taken to obtain proper division and description of the two strokes to further discrimination. In the recognition stage we combined syntactic analysis with statistical calculation. The other approach is for verifying offline handwritten Chinese signatures. Local connection properties are fully employed and the weighted distances are calculated on the whole signature image. Experiments results show that using the proposed matching methods increased the recognition rate and improved the reliability of our OCR system and is also helpful for verification of handwritten Chinese signatures. Pattern recognition, matching, handwritten character image, variation, measure, signature verification.</div>
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