Weld Seam Extraction Method of Radiographic Image Based on Beetle Algorithm and Mathematical Morphology

Abstract

The invention discloses a method for extracting welding seams of radiographic images based on beetle whiskers algorithm and mathematical morphology. Firstly, the radiographic images are preprocessed, grayscaled to obtain grayscale images, and two-dimensional self-adaptive Wiener filter processing is performed at the same time. ; Then threshold the gray-scale image, use the beetle-beetle optimization algorithm and clustering idea to find the best threshold for binarization of the ray image, and perform threshold segmentation on the ray gray-scale image to be segmented according to the optimal threshold searched to obtain Binarize the image; finally extract the weld edge of the radiographic image, perform denoising, object deletion and boundary extraction on the binarized image, so as to obtain the weld edge of the radiographic image. The invention combines the beetle beetle optimization algorithm with the clustering idea, can quickly and effectively obtain the binary image of the ray weld, and at the same time organically combines a variety of basic operations of binary morphology, which is suitable for weld images The advanced edge extraction can extract smooth, continuous weld edges that are not disturbed by defect areas.

Description

technical field

[0001] The invention belongs to the technical field of radiography detection image defect type identification, and in particular relates to a method for extracting welding seams of radiography images based on the beetle beetle algorithm and mathematical morphology. Background technique

[0002] Radiographic testing is an important non-destructive testing method for detecting internal defects of welds. Usually, ray is used to irradiate the workpiece to be tested, and the radiograph corresponding to the internal defects and structure of the workpiece is obtained for defect detection. Traditional radiographic film evaluation mainly relies on manual work, but manual film review is highly subjective, poorly consistent, and labor-intensive. Therefore, the use of automatic identification technology for radiographic inspection of welding defects to assist film reviewers to complete defect identification has become the focus of current research. Since the weld defects...

Images