Abstract：Metal thin film materials are prone to interface damage in practical applications, and the image damage area is difficult to determine under complex environmental backgrounds. Therefore, a rapid detection method for interface damage of metal thin film materials under complex environmental backgrounds is proposed. Perform grayscale processing on interface images of metal thin film materials in complex environmental backgrounds. Determine the damaged area of the metal thin 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 interface to obtain the damage detection results. The experimental results show that the proposed method can improve the image processing effect of metal thin film materials, improve the accuracy and efficiency of damage detection, and has high practical application value.
2024, Vol. 31 