基于双阈值自适应分割的轴承滚子表面缺陷提取技术研究

A Novel Bearing Roller Surface Defect Extraction Method Based on Double Threshold Adaptive Segmentation

针对工业缺陷检测中提取的缺陷存在不完整、处理速度过慢等问题,本文提出一种基于双阈值自适应分割的缺陷提取算法。根据实际工件的直方图,拟合得到标准直方图,而后利用实际工件的直方图与标准直方图自适应分析,快速定位出双边的误差阈值,从而避免高灰度缺陷或低灰度缺陷的漏检问题。实验结果表明,本文所提方法能够有效提高缺陷提取的完整性和准确性,并具备良好的处理速度。

Aiming at the problems of incomplete defects and slow processing speed in the detection of industrial defects, this paper proposes a defect extraction algorithm based on double threshold adaptive segmentation. According to the histogram of the actual workpiece, the standard histogram is obtained by fitting, and then the histogram of the actual workpiece and the standard histogram adaptive analysis are used to quickly locate the bilateral error threshold, thus avoiding high gray scale defects or low gray missing detection of degree defects. The experimental results show that the proposed method can effectively improve the integrity and accuracy of defect extraction and has a good processing speed.