Handwriting signal processing front-end for handwriting recognizers
US5577135A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Mar 1, 1994 |
| Grant date | Nov 19, 1996 |
| Priority date | — |
| Expiry date | Mar 1, 2014 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/23
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A handwriting signal processing front-end method and apparatus for a handwriting training and recognition system which includes non-uniform segmentation and feature extraction in combination with multiple vector quantization. In a training phase, digitized handwriting samples are partitioned into segments of unequal length. Features are extracted from the segments and are grouped to form feature vectors for each segment. Groups of adjacent from feature vectors are then combined to form input frames. Feature-specific vectors are formed by grouping features of the same type from each of the feature vectors within a frame. Multiple vector quantization is then performed on each feature-specific vector to statistically model the distributions of the vectors for each feature by identifying clusters of the vectors and determining the mean locations of the vectors in the clusters. Each mean location is represented by a codebook symbol and this information is stored in a codebook for each feature. These codebooks are then used to train a recognition system. In the testing phase, where the recognition system is to identify handwriting, digitized test handwriting is first processed as in the …
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.