An adaptive morphological algorithm to segment Chinese square seal in bank check image

摘要

In this paper, an adaptive morphological segmentation algorithm is proposed to extract a binary Chinese square seal from a bank check image. The grayscale Chinese square seal is extracted from the color bank check image according to the color information. Different Chinese characters have different stroke features and background evenness. To process each character in the square seal respectively, the extracted square seal is divided into four sub-squares. The background across each sub-square of the grayscale seal image is smoothed by top-hat transformation. The size of structuring element in top-hat transformation might have a great influence on the segmentation. The optimal size of the structuring element for the top-hat transformation on each sub-square is iteratively estimated according to the local foreground area. Each top-hat processed sub-square is binarized by Otsu's method. In each binary sub-square, holes smaller than a threshold are filled which is proportional to the ratio of the foreground area to the area of the whole sub-square. The experiment result shows that the proposed algorithm can correctly segment Chinese characters with intricate and dense strokes in a bank check square seal. Adhesion and incompleteness distortions in the segmentation results are reduced, even when the original square seal has a poor quality.