Automatic style clustering of printed characters in form images

Changsong Liu; Xiaoqing Ding

doi:10.1117/12.588138

17 January 2005 Automatic style clustering of printed characters in form images

Changsong Liu, Xiaoqing Ding

Proceedings Volume 5676, Document Recognition and Retrieval XII; (2005) https://doi.org/10.1117/12.588138
Event: Electronic Imaging 2005, 2005, San Jose, California, United States

Abstract

Style is an important feature of printed or handwritten characters. But it is not studied thoroughly compared with character recognition. In this paper, we try to learn how many typical styles exist in a kind of real world form images. A hierarchical clustering method has been developed and tested. A cross recognition error rate constraint is proposed to reduce the false combinations in the hierarchical clustering process, and a cluster selecting method is used to delete redundant or unsuitable clusters. Only a similarity measure between any patterns is needed by the algorithm. It is tested on a template matching based similarity measure which can be extended to any other feature and distance measure easily. The detailed comparing on every step’s effects is shown in the paper. Total 16 kinds of typical styles are found out, and by giving each character in each style a prototype for recognition, a 0.78% error rate is achieved by recognizing the testing set.

Citation Download Citation

Changsong Liu and Xiaoqing Ding "Automatic style clustering of printed characters in form images", Proc. SPIE 5676, Document Recognition and Retrieval XII, (17 January 2005); https://doi.org/10.1117/12.588138

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