在光学字符识别（OCR）图象扫描输入的过程中，扫描图象或多或少会出现某种程度的倾斜，这种图象的倾斜不仅会给下一步字符的切割造成困难，也影响最终的字符识别精度，通常情况下，为避免用户重新扫描，可以通过软件方法对图象进行矫正，为此提出一种利用Hough变换进行图象倾斜矫正的方法，为克服Hough变换计算量大的缺点，该方法采用了变分辨率图象金字塔策略，实验结果表明，该方法能快速准确测量出扫描图象的倾斜角度，并且具有很高的抗噪声性和应用适应性。

In process of OCR image scanning input, images may slant somehow. Severe image slant makes character segmentation next step difficult and lowers overall recognition accuracy of the system. Normally, in order to improve recognition accuracy and save image rescanning time, software correction is used to correct the slant before next step recognition processes of OCR are executing. This paper presents a novel slant correction method called Hough Transform OCR Image Slant Correction Method. The method uses Hough Transform to estimate the slant of scanning images. Because of heavy computing burdens of Hough Transform, the method employs Image Pyramid Processing to overcome the defeat of Hough Transform. Horizontal edge extracting processing is also used to speed the estimating process and to improve estimating accuracy. A great many artificial images and raw scanning images are used to test performances of the methodology. Experiment results show that the method can measure out slanting degree of scanning image efficiently and accurately just in a few seconds, and bears high noise endurance and application adaptability.