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A novel method to convert color/multi-spectral images to gray-level images isintroduced to increase the performance of document binarization methods. Themethod uses the distribution of the pixel data of the input document image in acolor space to find a transformation, called the dual transform, which balancesthe amount of information on all color channels. Furthermore, in order toreduce the intensity variations on the gray output, a color reductionpreprocessing step is applied. Then, a channel is selected as the gray valuerepresentation of the document image based on the homogeneity criterion on thetext regions. In this way, the proposed method can provide aluminance-independent contrast enhancement. The performance of the method isevaluated against various images from two databases, the ICDAR'03 RobustReading, the KAIST and the DIBCO'09 datasets, subjectively and objectively withpromising results. The ground truth images for the images from the ICDAR'03Robust Reading dataset have been created manually by the authors.

A maximal-information color to gray conversion method for document  images: Toward an optimal grayscale representation for document image  binarization