Image analysis – Learning systems – Trainable classifiers or pattern recognizers
Patent
1995-04-28
1998-01-06
Mancuso, Joseph
Image analysis
Learning systems
Trainable classifiers or pattern recognizers
395 20, G06R 962
Patent
active
057063648
ABSTRACT:
A method for producing, or training, a set of character templates uses as the source of training samples an image source of character images, called glyphs, that are not previously segmented or isolated for training. Also used is a labeled glyph position data structure that includes, for each glyph in the image source, a glyph image position in the image source associating an image location of the glyph with a character label paired with the glyph image position that indicates the character in the character set being trained. The labeled glyph position data is used to identify a collection of glyph sample image regions in the image source for each character in the character set; each glyph sample image region is large enough to contain a glyph and typically contains adjacent glyphs for other characters. The invention mathematically characterizes the template construction problem using unsegmented samples as an optimization problem that optimizes a function that represents the set of character templates being trained as an ideal image to be reconstructed to match the input image. The method produces all of the character templates contemporaneously by using a novel pixel scoring technique that implements an approximation of a maximum likelihood criterion subject to a constraint on the templates produced which holds that foreground pixels in adjacently positioned character images have substantially nonoverlapping foreground pixels. The character templates produced may be binary templates or arrays of pixel color probability values, and may also have substantially disjoint supports, such that adjacently imaged templates have substantially no overlapping foreground pixels.
REFERENCES:
patent: 3233219 (1966-02-01), Atrubin et al.
patent: 4769716 (1988-09-01), Casey et al.
patent: 5303313 (1994-04-01), Mark et al.
patent: 5321773 (1994-06-01), Kopec et al.
patent: 5438630 (1995-08-01), Chen et al.
patent: 5440651 (1995-08-01), Martin
patent: 5469512 (1995-11-01), Fujita et al.
patent: 5526444 (1996-06-01), Kopec et al.
patent: 5542006 (1996-07-01), Shustorovich et al.
patent: 5566247 (1996-10-01), Watanabe et al.
patent: 5577166 (1996-11-01), Mizuno
National Science Foundation (NSF) Grant Proposal for NSF Program Digital Libraries NSF 93-141 Feb. 4, 1994, submitted by the Regents of the University of California, Berkeley, document date Jan. 24, 1994, p. i-xi, 2-5, 36-37, 101, and 106.
G. Kopec, "Least-Squares Font Metric Estimation from Images", in IEEE Transactions on Image Processing, Oct., 1993, pp. 510-519.
G. Kopec and P. Chou, "Document Image Decoding Using Markov Source Models." in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, No. 6, Jun. 1994, pp. 602-617.
E. Levin and R. Pieraccini, "Dynamic planar warping for optical character recognition," in Proceedings of the 1992 International Conference on Acoustics, Speech and Signal Processing (ICASSP), San Francisco, California, Mar. 23-26, 1992, pp. III-149-III-152.
R. Rubenstein, Digital Typography: An Introduction to Type and Composition for Computer System Design, Addison-Wesley, 1988, pp. 115-121.
Adobe-Systems, Inc. Postscript Language Reference Manual, Addison-Wesley, 1985, pp. 95-96.
A. Kam and G. Kopec, "Separable source models for document image decoding", conference paper presented at IS&T/SPIE 1995 Intl. Symposium on Electronic Imaging, San Jose, CA, Feb. 5-10, 1995.
A. Kam, "Heuristic Document Image Decoding Using Separable Markov Models", S.M. Thesis, Massachusetts Institute of Technology, Cambridge, MA, Jun., 1993.
P.A. Chou and G.E. Kopec, "A Stochastic Attribute Grammar Model of Document Production and Its Use in Document Image Decoding", conference paper presented at IS&T/SPIE 1995 Intl. Symposium on Electronic Imaging, San Jose, CA, Feb. 5-10, 1995.
Chou Philip Andrew
Kopec Gary E.
Bares Judith C.
Mancuso Joseph
Xerox Corporation
LandOfFree
Method of producing character templates using unsegmented sample does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Method of producing character templates using unsegmented sample, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Method of producing character templates using unsegmented sample will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-2336334