Title :
Robust text detection from binarized document images
Author :
Okun, Oleg ; Yan, Yu ; Pietikäinen, Matti
Author_Institution :
Dept. of Electr. Eng., Oulu Univ., Finland
Abstract :
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.
Keywords :
character recognition; document image processing; image colour analysis; binarized document images; binary image; character recognition; color images; connected component analysis; inverted text; normal text; skew angles; text detection; Gray-scale; Image analysis; Image color analysis; Information resources; Information retrieval; Machine vision; Optical character recognition software; Parameter estimation; Robustness; Text analysis;
Conference_Titel :
Pattern Recognition, 2002. Proceedings. 16th International Conference on
Print_ISBN :
0-7695-1695-X
DOI :
10.1109/ICPR.2002.1047795