一种改进的维吾尔文图像倾斜校正方法

摘要

在维吾尔文扫描过程中，输入的文档不可避免地会发生倾斜现象，而现有的方法只进行了初步的倾斜校正。针对上述情况，同时为了方便维文图像的切分和识别工作，提出将基于凸多边形的最小面积外接矩形法和基线拟合法相结合的检测和校正图像方法。首先利用基于凸多边形的最小面积外接矩形法实现初步的倾斜校正，然后提取一行文本后采取基线拟合的方法实现文本行的单独校正，最后把校正过的所有文本行整合成一个文档。实验结果表明，该方法是行之有效的采用，该方法比现有方法在字母切分的准确率上平均提高约5%，最高提高约7%。%In Uighur text scanning process, the input document inevitably occur tilt function, however, we have only carried on the preliminary tilt correction using the existing method. In view of the above situation, at the same time in order to facilitate the segmentation and recognition of Uighur character scanning this paper proposed one approach that combining minimum-area bounding rectangle method based on the convex polygon with baseline fitting method to detect and correct text. Firstly used the minimum-area bounding rectangle method based on the convex polygon to realize the initial correction. Then extracted a line of the text and used baseline fitting method to correct the tilted text individually, finally, integrated the corrected text lines into a document. The existing methods only carried out preliminary tilt correction. The experimental results show that this method is accurate and effective, using our scheme can obtain a general increase in the accuracy of character segmentation by about 5%compared to the existing methods, and get a highest accuracy up to 7%.