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.
Automatic filter selection using image quality assessment
2003-01-01
232237 byte
Conference paper
Electronic Resource
English
Automatic Filter Selection Using Image Quality Assessment
British Library Conference Proceedings | 2003
|Efficient Content-Based Image Retrieval Using Automatic Feature Selection
British Library Conference Proceedings | 1995
|Wavelet filter selection by clustering of image measures
IEEE | 2003
|Wavelet Filter Selection by Clustering of Image Measures
British Library Conference Proceedings | 2003
|Modern Image Quality Assessment
TIBKAT | 2006
|