Interleaved segmental method for handwriting recognition
Patent 5878164 Issued on March 2, 1999. Estimated Expiration Date: 
October 8, 2017. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.
October 8, 2017. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.Patent ReferencesMethod for identifying plural connected figures Constraint driven-on line recognition of handwritten characters and symbols Multi-scale recognizer for hand drawn strokes Robust prototype establishment in an on-line handwriting recognition system Detecting line segments and predetermined patterns in an optically scanned document Patent #: 5129012 InventorsApplicationNo. 946876 filed on 10/08/1997US Classes:382/190, Feature extraction382/224ClassificationExaminersPrimary: Boudreau, Leo H.Assistant: Tadayon, Bijan International ClassesG06K 009/00229 230 231 312 313 314 315 301 317 321 216 218 290 181 182 200 183 184 201 185 186 202 187 188 207 189 190 209 191 192 208 194 195 204 197 198 199 203 AbstractA method of handwriting recognition is provided that combines the efficiency of a point oriented system and the shape information of a segment oriented system in an HMM based handwriting recognition system. The partial segmentation hypotheses obtained using the point oriented features in a conventional Viterbi search are augmented with scores based on segmental shape measurements made on the hypothesized segments. In addition, a method for segmentation of a handwriting sample is accomplished by incorporating a feature to distinguish between continuous and not continuous strokes and influencing the indicated hypothesis score by adding a penalty to the contraindicated hypothesis score.Other References
Field of SearchLEARNING SYSTEMSNeural networks Network learning techniques (e.g., back propagation) Network structures Trainable classifiers or pattern recognizers (e.g., adaline, perceptron) Generating a standard by statistical analysis Alphanumerics IMAGE SEGMENTATION Distinguishing text from other regions Segmenting individual characters or words Separating touching or overlapping characters Segmenting hand-printed characters Counting intersections of scanning lines with pattern Electronic template Classification Cluster analysis Sequential decision process (e.g., decision tree structure) With a multilevel classifier Statistical decision process | |
