【作者】 朱军民； 黄磊； 刘昌平；

【Author】 Junmin Zhu, Lei Huang, Changping Liu Character Recognition Laboratory Institute of Automation Chinese Academy of Sciences Beijing 100080)

【机构】 中科院自动化所文字识别实验室；

【摘要】 图像二值化就是将一幅多个灰度级的图像转化为只有两个灰度级的图像,以便于数据的压缩、特征的突出以及图形的识别。由于实际问题很复杂,定义一种通用而有效的二值化方法几乎是不可能的,所以在图像处理的历史上,针对实际问题提出了很多种二值化的方法,他们在数学的表达形式和算法的本质意义上都各不相同。本文对常用11种二值化方法(4种全局方法和7种局部方法)进行全面的比较,以便于更好的被选择利用。更多还原

【Abstract】 Image Binarization concerns the thresholding of a gray-level image to a binary image in order to compress data, extrude feature and recognition. For the complex of the practice, it is difficult to design a general image binarization algorithm, which performs well in many contexts and captures the requirements of subsequent processing stage. Consequently, over the history of digital image processing a variety of image binarization algorithm have been devised which differ in their mathematical and algorithmic properties. In this paper, we have conducted a relatively exhaustive comparison of 11 image binarization techniques (4 global methods and 7 local methods).更多还原