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Proceedings Paper

Geometric transformation algorithm for character recognition using a gradient method
Author(s): Takeshi Kamimura; Masanori Mizoguchi
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Paper Abstract

This paper proposes a feedback process approach to shape transformation in OCR character recognition for achieving higher recognition rates. An input image is deformed by warping function so that the stroke in the input image and the corresponding stroke in the reference image will overlap each other as much as possible. Pattern matching between both images is accomplished at several blurring levels, and a gradient method is applied to obtain the optimal warping parameters for minimizing the distance between the images in each blurring level. Third order polynomials by expanding Affine transformations are used as warping functions. Two kinds of pattern matching experiments were carried out. First, the image generated from an original image by warping function with certain parameters was matched with the original image by the proposed method. Second, machine-printed character images of different fonts were used for pattern matching. Both experimental results show that the optimal warping parameters for global minimization of the distances were successfully determined by the combination of a coarse-to-fine pattern matching and a gradient method. The proposed method is applicable to a variety of shape compensations, based on other matching criteria.

Paper Details

Date Published: 1 August 1990
PDF: 12 pages
Proc. SPIE 1258, Image Communications and Workstations, (1 August 1990); doi: 10.1117/12.19955
Show Author Affiliations
Takeshi Kamimura, NEC Corp. (Japan)
Masanori Mizoguchi, NEC Corp. (Japan)

Published in SPIE Proceedings Vol. 1258:
Image Communications and Workstations
Walter Bender; Mitsunaga Saito, Editor(s)

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