一种针对畸变印刷品字符校正的多项式自寻优改进方法

目的针对畸变印刷品字符校正过程中无畸变先验知识、传统方法效率低且精度差的问题,提出一种以多项式自寻优改进算法为核心的字符校正方法。方法将待测字符区域视为小篇幅图像,通过初次校正确定畸变区域,以待测图像与标准图像的最小差分结果为优化目标,利用菌群算法在畸变区域中进行校正控制点的自寻优运算,从而建立校正函数对字符畸变区域进行校正,并通过Matlab仿真加以实现。结果该方法平均校正精度低于0.6像素,运行时间低于0.12 s,达到了对畸变字符快速准确校正的目的。结论该自寻优改进方法克服了人工操作的弊端,对畸变字符进行了有效校正,有助于提高后续缺陷检测的精度和效率。

A Polynomial Self-optimizing Method for the Character Correction of Distortion Prints

The work aims to propose a character correction method based on polynomial self-optimizing algorithm regarding the problems of no prior knowledge of the distortion, low efficiency of traditional method and poor accuracy in the correction process of distortion print characters. The character area to be detected was treated as a small image. The distortion region was determined by the initial correction. With the minimum difference result between the image to be tested and the standard image as the optimization target, the self-optimizing operation of the correction control point was carried out in distortion region by bacterial population algorithm, thereby establishing a correction function to correct the character distortion region, and finally it was realized by Matlab simulation. The mean correction accuracy of this method was less than 0.6 pixels, and the running time was less than 0.12 s, which achieved the purpose of fast and accurate correction of distortion characters. The self-optimizing method has overcome the shortcomings of manual operation and effectively corrected the distorted characters, which helps to improve the accuracy and efficiency of subsequent defect detection.