Card Images Binarization Based on Dual-Thresholding Identification

In this paper, an algorithm is proposed for card images binarization. It is performed by three steps: coarse binarization, refined binarization, and postprocessing. Firstly, it uses the traditional global thresholding approach to separate a card image into several sub-images, which can be classified into two classes: text sub-images with clear background and text sub-images with complicated background. Secondly, the dual-thresholding is applied to regenerate or retouch the sub-images. According to the characteristics of text candidate sub-image, the thresholding method is selected and applied on it. Finally, the postprocessing is performed on the binary image. Experimental results demonstrate that this approach highly improved the performance of the card image binarization system.