Method and apparatus for recognizing characters on a document

Image analysis – Histogram processing – For setting a threshold

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G06K 934

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049264907

ABSTRACT:
A method and apparatus for recognizing characters on a document, even if the document is skewed or not aligned with the axis of a typical segmentation apparatus such as a scanner. A plurality of rectangles are formed surrounding respective character images, with position data for each rectangle stored in a first table in which plural position data of the rectangles are arranged in order from the left-most rectangle to the right-most rectangle in the X direction of the XY coordinates of the image buffer. By determining the rectangles belonging to one character row in the first list and calculating the positions of the bottom left corners of the rectangles, skew of the document is calculated. Vertical positions of the rectangles compensated by the skew in the Y direction are calculated to transfer the position data of the rectangles belonging to the first character row to a second table. The image data surrounded by the rectangles specified by the position data in the second list are sequentially supplied to a character recognition unit.

REFERENCES:
Segmentation Methods for Recognition of Machine-printed Characters R. L. Hoffman, J. W. McCullough, pp. 153-165, IBM Journal of Research and Development, vol. 15, No. 2, 3/71.
Document Analysis System, K. Y. Wong, R. G. Casey, F. M. Wahl, pp. 647-656, IBM Journal of Research and Development, vol. 26, No. 6, 11/82.
A Processor-Based OCR System, R. G. Casey, C. R. Jih, IBM Journal of Research and Development, vol. 27, No. 4, 7/83, pp. 386-399.
Recursive Segmentation and Classification of Composite Character Patterns, R. G. Casey, G. Nagy, pp. 1023-1026, vol. 2, Proceedings from the 6th International Conference on Pattern Recognition, Munich, Germany, 10/19-22, 1982.
Unsupervised Construction of Decision Networks for Pattern Classification R. G. Casey, S. K. Chai, and K. Y. Wong, pp. 1256-1258, IEEE Seventh International Conference on Pattern Recognition, 7/30-8/2/84, Montreal, Canada.

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