Automatic handwriting recognition using both static and dynamic

Details Automatic handwriting recognition using both static and dynamic Automatic handwriting recognition using both static and dynamic

1993-01-27

1996-02-13

Boudreau, Leo

Image analysis

Pattern recognition

On-line recognition of handwritten characters

382188, 382228, G06K 900

Patent

active

054917581

ABSTRACT:
Methods and apparatus are disclosed for recognizing handwritten characters in response to an input signal from a handwriting transducer. A feature extraction and reduction procedure is disclosed that relies on static or shape information, wherein the temporal order in which points are captured by an electronic tablet may be disregarded. A method of the invention generates and processes the tablet data with three independent sets of feature vectors which encode the shape information of the input character information. These feature vectors include horizontal (x-axis) and vertical (y-axis) slices of a bit-mapped image of the input character data, and an additional feature vector to encode an absolute y-axis displacement from a baseline of the bit-mapped image. It is shown that the recognition errors that result from the spatial or static processing are quite different from those resulting from temporal or dynamic processing. Furthermore, it is shown that these differences complement one another. As a result, a combination of these two sources of feature vector information provides a substantial reduction in an overall recognition error rate. Methods to combine probability scores from dynamic and the static character models are also disclosed.

REFERENCES:
patent: 4903312 (1990-02-01), Sato
patent: 5005205 (1991-04-01), Ellozy et al.
patent: 5058182 (1991-10-01), Kuan et al.
patent: 5105468 (1992-04-01), Guyon et al.
patent: 5111512 (1992-05-01), Fan et al.
patent: 5265174 (1993-11-01), Nakatsuka
patent: 5343537 (1994-08-01), Bellegarda et al.
Translation of DE3822671A1.
Charles C. Tappert, Ching Y. Suen, Toru Wakahara, "The State of the Art in On-Line Handwriting Recognition", IEEE, vol. 12, No. 8, pp. 787-808, Aug. 1990.

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