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Proceedings Paper

Background feature descriptor for offline handwritten numeral recognition
Author(s): Delie Ming; Hao Wang; Tian Tian; Feiran Jie; Bo Lei
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Paper Abstract

This paper puts forward an offline handwritten numeral recognition method based on background structural descriptor (sixteen-value numerical background expression). Through encoding the background pixels in the image according to a certain rule, 16 different eigenvalues were generated, which reflected the background condition of every digit, then reflected the structural features of the digits. Through pattern language description of images by these features, automatic segmentation of overlapping digits and numeral recognition can be realized. This method is characterized by great deformation resistant ability, high recognition speed and easy realization. Finally, the experimental results and conclusions are presented. The experimental results of recognizing datasets from various practical application fields reflect that with this method, a good recognition effect can be achieved.

Paper Details

Date Published: 2 December 2011
PDF: 8 pages
Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 80041N (2 December 2011); doi: 10.1117/12.921098
Show Author Affiliations
Delie Ming, Huazhong Univ. of Science and Technology (China)
Hao Wang, Huazhong Univ. of Science and Technology (China)
Tian Tian, Huazhong Univ. of Science and Technology (China)
Feiran Jie, Science and Technology on Electro-optic Control Lab. (China)
Bo Lei, Science and Technology on Electro-optic Control Lab. (China)


Published in SPIE Proceedings Vol. 8004:
MIPPR 2011: Pattern Recognition and Computer Vision
Jonathan Roberts; Jie Ma, Editor(s)

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