System and method for automatic handwriting recognition with a writer-independent chirographic label alphabet
US5644652A · kind A · utility
Assignee
Inventors
Key dates
| Filing date | Apr 19, 1995 |
| Grant date | Jul 1, 1997 |
| Priority date | — |
| Expiry date | Apr 19, 2015 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/295
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An automatic handwriting recognition system wherein each written (chirographic) manifestation of each character is represented by a statistical model (called a hidden Markov model). The system implements a method which entails sampling a pool of independent writers and deriving a hidden Markov model for each particular character (allograph) which is independent of a particular writer. The HMMs are used to derive a chirographic label alphabet which is independent of each writer. This is accomplished during what is described as the training phase of the system. The alphabet is constructed using supervised techniques. That is, the alphabet is constructed using information learned in the training phase to adjust the result according to a statistical algorithm (such as a Viterbi alignment) to arrive at a cost efficient recognition tool. Once such an alphabet is constructed a new set of HMMs can be defined which more accurately reflects parameter typing across writers. The system recognizes handwriting by applying an efficient hierarchical decoding strategy which employs a fast match and a detailed match function, thereby making the recognition cost effective.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.