摘要
根据中文支票识别的预处理过程中提取特定目标的需要,研究了多种二值化算法在预处理中的效果。通过分析2000张中文支票灰度图像的直方图,找到了可以用于图像分割的直方图梯度值信息,基于该梯度值信息,提出了一种用于提取支票图像中金额栏外围框线的二值化算法,使得支票灰度图像中的待提取框线更加清晰、凸出,更加易于定位。在中文支票预处理环境下,所提出的二值化算法在与其它多种二值化算法的对比测试中,表现出了更好的效果和更高的效率。
In order to meet the requirements of preprocessing of Chinese cheque image recognition, this paper studied several binarization algorithms. After analyzing the histograms of gray-level images of 2000 cheques, we found a clue, maximum gradient, in histogram of gray-level cheque image, which can be used for segmenting image and extracting given object parallel-line of amount field. With the clue, we developed a new binarization algorithm which makes the paral- lel-line of amount field more obvious and easier to be located in binarization image. Comparing with several other commonly used binarization algorithms,the algorithm proposed by the paper has been proven to be more feasible and advanced in the simulating tests.
出处
《计算机科学》
CSCD
北大核心
2009年第12期282-284,共3页
Computer Science
关键词
中文支票识别
二值化
直方图
梯度值
Chinese cheque image recognition, Binarization, Histogram, Gradient
