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Automatic Filter Selection Using Image Quality Assessment
Edinburgh, Scotland August 03-August 06
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDAR.2003.1227717Seventh International Conference on D ...
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Andrea Souza, Concordia University
Mohamed Cheriet, Concordia University; University of Qu?bec
Satoshi Naoi, Fujitsu Labs Ltd.
Ching Y. Suen, Concordia University
We present a method for automatically selecting the best filter to treat poor quality printed documents using image quality assessment. We introduce five quality measures to obtain information about the quality of the images, and morphological filters to improve their quality. A training set of 370 images was used to develop the system. Experimental results on the test set show a significant improvement in the recognition rate from 73.24% using no filter at all to 93.09% after applying a filter that was automatically selected.
Citation:
Andrea Souza, Mohamed Cheriet, Satoshi Naoi, Ching Y. Suen, "Automatic Filter Selection Using Image Quality Assessment," icdar, vol. 1, pp.508, Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 1, 2003
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