摘要
金属膜材料在实际应用中容易出现表面损伤,且材料所处的环境复杂背景较为复杂,导致图像损伤区域难以确定,因此提出复杂环境背景下金属膜材料表面损伤快速检测方法。对复杂环境背景下的金属膜材料表面图像展开灰度化处理,通过计算图像灰度分布方差和均值确定金属膜材料图像损伤区域,采用自适应分割方法将损伤区域从原始图像中分割出来,利用拉普拉斯算子对损伤区域展开锐化处理。通过灰度共生矩阵提取锐化处理后损伤区域特征,将其输入金属膜材料表面损伤快速检测函数中,得到损伤检测结果。实验结果表明,所提方法能够提高金属膜材料图像处理效果,提高损伤检测精度和效率,具有较高的实际应用价值。
Metal film materials are prone to surface damage in practical applications,and the complex environment and background in which the materials are located make it difficult to determine the damage area in the image.Therefore,a rapid detection method for surface damage of metal film materials under complex environmental backgrounds is proposed.Perform grayscale processing on surface images of metal film materials in complex environmental backgrounds.Determine the damaged area of the metal film material image by calculating the variance and mean of the image grayscale distribution.Use adaptive segmentation methods to segment the damaged area from the original image,and use Laplace operator to sharpen the damaged area.Extract the features of the sharpened damaged area through the gray level co-occurrence matrix,and input them into the rapid damage detection function of the metal film material surface to obtain the damage detection results.The experimental results show that the proposed method can improve the image processing effect of metal film materials,improve the accuracy and efficiency of damage detection,and has high practical application value.
作者
李一帆
侯纪伟
LI Yifan;HOU Jiwei(School of Mathematical Sciences,Nanjing Tech University,Nanjing 211816,Jiangsu,China)
出处
《金属功能材料》
CAS
2024年第2期100-105,共6页
Metallic Functional Materials
基金
江苏省自然科学基金项目(071JS88105)。
关键词
金属膜材料表面
图像增强
图像分割
灰度共生矩阵
损伤检测
metal film material surface
image enhancement
image segmentation
gray level co-occurrence matrix
damagedetection
