Neural network based character position detector for use in opti

Image analysis – Learning systems – Neural networks

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387159, 387173, 395 21, G06K 962

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055420060

ABSTRACT:
Apparatus, and an accompanying method, for use in an optical character recognition (OCR) system (5) for locating, e.g., center positions ("hearts") of all desired characters within a field (310; 510) of characters such that the desired characters can be subsequently recognized using an appropriate classification process. Specifically, a window (520) is slid in a step-wise convolutional-like fashion (520.sub.1, 520.sub.2, 520.sub.3) across a field of preprocessed, specifically uniformly scaled, characters. Each pixel in the window is applied as an input to a positioning neural network (152) that has been trained to produce an output activation whenever a character "heart" is spatially coincident with a pixel position within an array (430) centrally located within the window. As the window is successively moved across the field, in a stepped fashion, the activation outputs of the neural network are averaged, on a weighted basis, for each different window position and separately for each horizontal pixel position in the field. The resulting averaged activation output values, typically in the form of a Gaussian distribution for each character, are then filtered, thresholded and then used, via a weighted average calculation with horizontal pixel positions being used as the weights, to determine the character "heart" position as being the center pixel position in the distribution.

REFERENCES:
patent: 4933977 (1990-06-01), Ohnishi et al.
patent: 5052043 (1991-09-01), Gaborski
patent: 5105468 (1992-04-01), Guyon et al.
patent: 5119438 (1992-06-01), Ueda et al.
patent: 5131073 (1992-07-01), Furuta et al.
patent: 5151951 (1992-09-01), Ueda et al.
patent: 5239593 (1993-08-01), Wittner et al.
patent: 5245672 (1993-09-01), Wilson et al.
patent: 5299269 (1994-03-01), Gaborski et al.
patent: 5440651 (1995-08-01), Martin
A. Shustorovich, "A Subspace Projection Approach to Feature Extraction: The Two-Dimensional Gabor Transform for Character Recognition" to appear in Neural Networks, 1994, vol. 7, No. 5.
Y. Bengio et al., "Globally Trained Handwritten Word Recognizer using Spatial Representation, Convolutional Neural Networks. and Hidden Markov Models", Proceedings of 1993 Conference on Neural Information Processing Systems--Natural and Synthetic, Nov. 29-Dec. 2, 1993, Denver, Colorado, pp. 937-944.
A. Gupta et al., "An Integrated Architecture for Recognition of Totally Unconstrained Handwritten Numerals", International Journal of Pattern Recognition and Artificial Intelligence, 1993, vol. 7, No. 4, pp. 757-773.
G. Martin et al., "Learning to See Where and What: Training a Net to Make Saccades and Recognize Handwritten Characters" (1993), appears in S. J. Hanson et al. (eds.), Advances in Neural Information Processing Systems, vo 1. 5, pp. 441-447 (Morgan Kaufmann Publishers, San Mateo, CA).
J. Keeler et al., "A Self-Organizing Integrated Segmentation and Recognition Neural Net", appears in J. E. Moody et al. (eds.), Advances in Neural Information Processing Systems, 1992, vol. 4, pp. 496-503.
J. A. Freeman et al., Neural Networks--Algorithms, Applications and Programming Techniques, pp. 89-125 (copyright 1991: Addison-Welsey Publishing Company, Inc.).
J. Daugman, "Complete Discrete 2-D Gabor Transforms by Neural Networks for Image Analysis and Compression", IEEE Transactions on Acoustics, Speech and Signal Processing, 1988, vol. 36, No. 7, pp. 1169-1179.
D. E. Rumelhart et al., Parallel Distributed Processing, vol. 1, pp. 328-330 (copyright 1988, MIT Press).

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