A New Method of Contrast Normalization for Verification of Extracted Video Text Having Complex Backgrounds

One of the difficulties of extracting text contained in images or videos comes from the variation of the grayscale values of the text and backgrounds. In this paper we propose a new method to normalize the contrast between text characters and backgrounds so that a trained machine learning tool can verify characters of grayscale values that have never been seen before. Experiments show that the proposed method used in training either a multilayer perceptrons or a support vector machine yields better text verification comparing with other typical contrast measures.

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