Automatic Evaluation of Document Binarization Results

Most of the document binarization techniques have many parameters that can initially be specified. Usually, subjective document binarization evaluation, employs human observes for the estimation of the best parameter values of the techniques. Thus, the selection of the best values for these parameters is crucial for the final binarization result. However, there is not any set of parameters that guarantees the best binarization result for all document images. It is important, the estimation of the best values to be adaptive for each one of the processing images. This paper proposes a new method which permits the estimation of the best parameter values for each one of the document binarization techniques and also the estimation of the best document binarization result of all techniques. In this way, document binarization techniques can be compared and evaluated using, for each one of them, the best parameter values for every document image.