霍夫变换
人工智能
计算机科学
稳健性(进化)
像素
计算机视觉
印刷电路板
机器视觉
预处理器
图像分割
特征提取
图像质量
算法
分割
图像(数学)
操作系统
基因
化学
生物化学
作者
Min Qi,Yanan Wang,Yanshuo Chen,Hongjuan Xin,Yuelei Xu,Hongying Meng,Aili Wang
标识
DOI:10.1117/1.jei.32.1.011002
摘要
A highly efficient circle positioning algorithm, called the two-step optimization Hough transform (TSHT), based on multi-resolution segmentation is proposed to solve the problems of the offset Hough transform, namely, its large memory overhead, long time consumption, and low recognition accuracy. First, using the image feature of the printed circuit board (PCB) circular identifier, the target circle is obtained using adaptive image preprocessing, and then, images of an acceptable quality are separated by shape quality inspection to improve their robustness. Second, using effective interval sampling strategies and gradually controlling the accumulative interval of parameters, the TSHT algorithm reduces the memory overhead and quickly locates the center at the pixel level. Finally, the center at the sub-pixel level is found by the least-squares method for circle fitting. The experiments prove that TSHT, as a result of its high robustness, strong anti-noise capability, fast recognition speed, and accuracy, can be successfully applied to a vision positioning system of a solder paste printing machine.
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