针对传统的倾斜矫正与分割算法对不同类型的字符图像处理效果各异的问题，本文提出了一种改进的算法，加入了新的倾斜角度确定准则、阈值动态调整以及区域后处理,不仅解决了传统方法易受噪声和复杂背景干扰、可操作性差的问题，而且也有效地实现了字符图像的倾斜矫正与分割。实验结果表明，尽管新算法在像素点判断次数上多于最大类间方差算法，但分割效果明显优于最大类间方差和文献［7］的阈值分割算法。同时，本算法较传统算法更加具有鲁棒性，运行时间可以满足实时性的要求。

In allusion to the problem that the traditional algorithms which solve slant correction and segmentation have different effects on different types of character images, a new algorithm is presented. It improves the traditional algorithms by adding a new slant angle determination rule, by adjusting the threshold dynamically and postprocessing the regions. The new algorithm not only solves the problem that the traditional method is easily interfered by noise and complicated background and it has bad operability, but also realizes slant correction and segmentation in character images. The experimental results show that although the new algorithm’s numbers produced by the measurement of pixels are more than the algorithm of maximum between cluster variances, its segmentation effect is significantly better than the algorithm of maximum between cluster variances and threshold segmentation algorithm proposed by literature［7］, Meanwhile,the new algorithm is more robust than the traditional methods, and the running time meets the requirement of realtimeness completely.