| 摘要 |
Character recognition method and system that identifies an input character as being a unique member of a defined character set. Specifically, a character bit-map of an input character is first generated. Thereafter, a character recognition procedure processes the character bit-map to generate a set of confidence measures one for each of the members of the character set. The confidence measures represent the degree of confidence that the input character corresponds to the members of the character set. A test is then made to determine if the confidence measure with the highest degree of confidence is acceptable. If there is an acceptable confidence measure, the member of the character set with the acceptable confidence measure is reported as the output character. If there is no acceptable confidence measure, a number of characters with the highest confidence measures are identified as candidates. Also, the character bit-map is analyzed further to obtain stroke-endpoint information which is then compared to a learned endpoint database having a number of character string-signature pairs. If there is a match between a database string and a candidate character, the match is used to report an output character. Endpoint location and orientation are obtained by modeling the bit-map as a charge distribution. A potential profile is constructed and thresholded and the results clustered into regions to obtain endpoint location information. The gradient of the potential profile is used to obtain endpoint orientation information. |
