摘要
图像分割是图像理解与分析的基础。在众多的图像分割方法中,阈值法计算简单,具有较高的运算效率,是图像分割中广泛采用的方法。选取适当的阈值是阈值法的关键。OTSU法(最大类间方差法)被认为是阈值自动选取方法的最优方法之一。由于焊缝图像常出现大面积的灰度不均匀,OTSU方法不能有效地分割出焊缝间隙。在充分分析焊缝图像以及OTSU方法的基础上,提出一种改进的自适应阈值选取方法。实验证明该方法具有较强的自适应性,能有效地分割焊缝图像。
Image segmentation is important in comprehension and analysis of image.Threshold segmentation is widely used in image segmentation because of its simplicity and high efficiency.How to get the fine threshold is the key of image threshold segmentation.The OTSU algorithm(Maximization of interclass variance)is one of the superior threshold selection methods.When the OTSU method is used for welding seam image segmentation,the quality of image segmentation is not good because the welding seam images often appear gray level asymmetry of large area.Based on welding seam image analysis and OTSU algorithm,an improved method of adaptive threshold selection is proposed.The experiment results show that the new method is strongly adaptable and efficient for welding seam image segmentation.
出处
《电焊机》
2003年第9期24-27,共4页
Electric Welding Machine
基金
国家自然科学基金资助项目(50175027)
广东省自然科学基金资助项目(0133002)
教育部博士点基金资助项目(20010561013)
关键词
图像分割
最大类间方差法
焊缝图像
image segmentation
Maximization of interclass variance
welding seam image
