基于机器视觉的轮胎胶料表面字符识别

针对目前轮胎胶料表面的5×7点阵喷码字符人工识别存在劳动强度大、效率低、智能化水平低等问题,提出了一种基于机器视觉的轮胎胶料表面字符识别方法,首先利用字符出现区域较为稳定且字符为黑底白字进行快速定位与背景分割、形态学操作消除干扰;然后创新性地运用简化垂直投影法配合字符宽度的阈值限制,并对"1"和"I"与其他字符宽度不同的特殊情况进行处理,实现字符分割;最后,采用基于标准相关匹配的模板匹配方法实现字符识别。实验结果表明,所提方法的字符识别准确率达到99.51%,达到了预期的识别效果。

Recognition of characters on tire rubber surface based on machine vision

At present, the 5×7 dot matrix spray-code character recognition on the surface of tire rubber has many problems, such as high labor intensity, low efficiency and low intelligence level. Based on machine vision, a novel character recognition method for tire rubber surface is proposed. Firstly, the character occurrence area is stable and the character is white on black background for fast positioning, background segmentation and using morphological manipulation to remove interference. Then, the simplified vertical projection method is innovatively used to fit the threshold of character width, and the special cases of "1"and "I" which are different from other character widths are processed to achieve character segmentation. Finally, the template matching method based on standard correlation matching is used to realize character recognition. Experimental results show that the accuracy of the proposed method is 99.51%, which achieves the expected recognition effect.