基于非线性预处理策略的文档图像二值化处理

Nonlinear Preprocessing Based Document Image Binarization

在许多对图像进行识别的应用中,如机票图像识别,芯片字符识别等,首先都要将图像进行二值化,转为黑白图像.但是由于一般扫描的图像都不是非常理想,直接二值化的效果并不好,通常都要经过一些预处理方法增强图像,去除在扫描过程中产生的噪声和形变,但使用线性的、空间不变的过滤器,去噪声的同时又会丢失边缘信息.因此笔者介绍了一种自适应的非线性预处理的方法,能够在去噪声的同时很好地进行边缘增强.

In many applications involving character recognition from digitized document images such as coupon and characters on chip, the input images are first binarized to form two-level images. However, direct binarization of such images often results in unsatisfactory performance because of the poor quality of the input images. Consequently, it is usual to preprocess such images in order to enhance the edges in the presence of noise and other types of distortions that occur during the scanning process. Edge enhancement and noise reduction are conflicting requirements for linear, space-invariant filters. This paper introduces a nonlinear method for preprocessing document images that can denoise and enhance the edges at the same time.