Abstract
In this paper, optimal Boolean filters are applied to enhance the binary document images corrupted with uniform noise or uniformly distributed distinct graphical patterns in the background. The performance and operation theory of optimal Boolean filters against other competitive techniques are compared. Experimental results show that the Boolean filters outperforms the morphology approach in extracting the text from overlapped text/background images. The feasibility of trained Boolean filters is also confirmed by experimental results in the case where the original image is not available.
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