The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Mar. 12, 2013
Filed:
Feb. 25, 2009
Jing-lian Gao, Guanghzou, CN;
Xinchun Huang, Guangzhou, CN;
Binghui Chen, Guangzhou, CN;
Anjin HU, Guangzhou, CN;
Muyu Cai, Guangzhou, CN;
Huaxing LU, Guangzhou, CN;
Zhipin Liu, Guangzhou, CN;
Zhiai Wang, Guangzhou, CN;
Fang Guo, Guangzhou, CN;
Jingping LI, Guangzhou, CN;
Honghui Wang, Guangzhou, CN;
Chuntao Tan, Guangzhou, CN;
Zhengwei Wu, Guangzhou, CN;
Jing-lian Gao, Guanghzou, CN;
Xinchun Huang, Guangzhou, CN;
Binghui Chen, Guangzhou, CN;
Anjin Hu, Guangzhou, CN;
Muyu Cai, Guangzhou, CN;
Huaxing Lu, Guangzhou, CN;
Zhipin Liu, Guangzhou, CN;
Zhiai Wang, Guangzhou, CN;
Fang Guo, Guangzhou, CN;
Jingping Li, Guangzhou, CN;
Honghui Wang, Guangzhou, CN;
Chuntao Tan, Guangzhou, CN;
Zhengwei Wu, Guangzhou, CN;
Guangdong Guobi Technology Co., Ltd, Guangzhou, CN;
Abstract
The present invention discloses a method for recognizing a handwritten character, which includes the following steps of: obtaining a coarse classification template and a fine classification template; receiving a handwritten character input signal from a user, gathering a discrete coordinate sequence of trajectory points of the inputted character, and pre-processing the discrete coordinate sequence; extracting eigenvalues and calculating a multi-dimensional eigenvector of the inputted character; matching the inputted character with the coarse classification template to select a plurality of the most similar candidate character classes; and matching the eigen-transformed inputted character with sample centers of the candidate character classes selected from the fine classification template, and determining the most similar character classes among the candidate character classes. The present invention further discloses a system for recognizing a handwritten character. The present invention can recognize an inputted character fast at a high recognition precision.