Handwriting signal processing front-end for handwriting recogniz

Details Handwriting signal processing front-end for handwriting recogniz Handwriting signal processing front-end for handwriting recogniz

1994-03-01

1996-11-19

Couso, Jose L.

Image analysis

Image compression or coding

Quantization

382187, G06K 936, G06K 900

Patent

active

055771351

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 training phase to generate feature-specific vectors from input frames. Multiple vector quantization is then performed on each feature-specific vector to represent the feature-specific vector using the codebook symbols that were generated for that feature during training. The resulting series of codebook symbols effects a reduced representation of the sampled handwriting data and is used for subsequent handwriting recognition.

REFERENCES:
patent: 4597101 (1986-06-01), Kishimoto et al.
patent: 5136663 (1992-08-01), Nishio
patent: 5202926 (1993-04-01), Miki
patent: 5226091 (1993-07-01), Howell et al.
patent: 5255090 (1993-10-01), Israelsen
patent: 5343537 (1994-08-01), Bellegarda
David E. Rumelhart, Theory to Practice: A Case Study--Recognizing Cursive Handwriting, preprint, p. 1-20 (1993).
Kundu, Amlan and Bahl, Paramrir, "Recognition of Handwritten Script: A Hidden Markov Model Based Approach", IEEE, NY, 1988.
Furvi, Sadaoki, "A VQ-Based Preprocessor Using Cepstral Dynamic Features for Speaker-Independent Large Vocabulary Word Recognition," IEEE, 1988.
Class, F., Kaltemeier, A., and Regel, P., "Soft-Decision Vector Quentization Based in the Dempster / Shafer theory", IEEE, 1991.
Constantinescu et al., "On-line Adaptive Vector Quantization with Variable Size Codebook Entries", IEEE, 1993, pp. 32-41.
Andrews et al., "A Mean-Removed Variation of Weighted Universal Vector Quantization for Image Coding", IEEE, 1993, pp. 302-308.
HO, Tin Kam, "Recognition of Handwritten Digits by Combining Independent Learning Vector Quantization", IEEE, 1993, pp. 818-821.

Affiliated with

Also associated with

Rating

Handwriting signal processing front-end for handwriting recogniz does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Handwriting signal processing front-end for handwriting recogniz, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Handwriting signal processing front-end for handwriting recogniz will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-547303