为了提高钢坯表面喷印字符分割的效果, 提出通过图像增强和滤波算法改善图像质量, 解决钢坯表面喷印字符图像的分割问题. 通过构造自适应阈值, 自动分割图像进行字符串定位, 并基于形态学处理、连通域分析设计了字符分割算法, 解决了图像中存在的黏连和断裂问题. 设计了一种掩膜保护字符的滤波算法, 解决了细线噪声干扰问题, 同时建立了相应的实验系统进行研究. 结果表明: 该算法效果较好, 对字符图像黏连、断裂情况分割的正确率分别达到了 99.6%, 98.3%, 对细线噪声干扰类样本分割的正确率达到了 97.9%.

To obtain better segmentation of painting character images on a billet surface, a algorithm is proposed to improve picture quality by image enhancement and filtering, and solve problems in the character image segmentation. An automatic adaptive threshold segmentation algorithm is developed to locate character strings. The algorithm is based on morphology, connected component analysis and twice division to solve the problem of adhesion and fracture present in the image. A filter with a character protection mask is proposed to deal with thin line noises. Experimental results show that the proposed algorithms have good performance for images with character adhesion and fractures, and achieve correct segmentation rates of 99.6% and 98.3%, respectively. The algorithms are also effective to solve the problems of thin line noises, achieving a correct segmentation rate of 97.9%.