计算机科学 ›› 2020, Vol. 47 ›› Issue (6A): 247-249.doi: 10.11896/JsJkx.191000049
杨志伟1, 戴铭2, 周智恒2
YANG Zhi-wei1, DAI Ming2 and ZHOU Zhi-heng2
摘要: 随着计算机视觉的高速发展,在产品检测方面,人工劳动力逐渐被机器视觉取代,特别是在工作人员不宜长期逗留的生产环境中,工业产品的表面缺陷自动检测是现代化工业的必然趋势。文中将缺陷检测看作一种特定的图像分割问题,将产品表面看作背景、以表面缺陷为前景来进行提取。在所提方法中,分割的主要依据是前景和背景的灰度分布直方图差异程度以及背景分布和先验背景分布的直方图相似程度;结合非参数统计活动轮廓模型和先验分布,以产品表面的灰度分布为背景的先验信息,构造对应的能量函数,然后最小化能量函数得到相应的水平集函数迭代方程,以更高效地进行缺陷检测。相关实验表明,所提出的缺陷检测方法在视觉上有较大提升,在检测正确率、虚警率和漏检率等数值指标上也有较大提升。
中图分类号:
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