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16th International Conference on Pattern Recognition (ICPR'02) - Volume 3
Robust Text Detection from Binarized Document Images
Quebec City, QC, Canada
August 11-August 15
ISBN: 0-7695-1695-X
Oleg Okun, University of Oulu
Yu Yan, University of Oulu
Matti Pietikäinen, University of Oulu
Many document images are rich in color and have complex background. To detect text from them, a standard approach utilizes both color and binary information. This often leads to time-consuming processing and requires a lot of parameters to be tuned. In contrast, we propose a new method for text detection using a binary image alone. The main virtues of our method include detection of both normal and inverted text and robustness to various font types, styles and sizes and small skew angles, combined with a moderate number of free parameters.
Citation:
Oleg Okun, Yu Yan, Matti Pietikäinen, "Robust Text Detection from Binarized Document Images," icpr, vol. 3, pp.30061, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 3, 2002
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