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Talking about scratch detection in machine vision
Author:Administrator   Published in:2020-01-14 17:27

In the manufacturing process of industrial products, many parts of equipment work in high-temperature and high-pressure environments. Complex loads, harsh operating environments, and high failure rates cause scratches on the product surface. This not only Will affect the appearance of the product and is more likely to reduce the quality of the product. Therefore, scratch detection is particularly important in the manufacturing process of industrial products.

When detecting the presence of scratches on a product, the scratch image appears to have a gray value at the scratch that differs from the gray value of the standard image here. First, the features of the scratch image are extracted and selected, and then the gray value of the scratch image is compared with the gray value of the standard image to determine whether the difference (the degree of difference between the gray values of the two pictures) exceeds the preset value. The set threshold range can be used to determine whether the product to be inspected is defective.

The basic analysis process of machine vision scratch detection is divided into three steps: first, the acquisition of images; second, determining whether there is a scratch on the surface of the detection product; finally, after determining that there are scratches on the analyzed image, extracting the scratches.

First, scratch detection generally adopts LED ring light direct dark field illumination. The ring light and the surface of the object are at a very small angle. This can highlight the gaps and protrusions of the measured object.  Therefore, scratches, textures, or engraving text, etc. It is enhanced, and I see more clearly.

Second, the collected images cannot provide information about the objects in the image. In order to obtain the object information in the image, must perform image segmentation. Image segmentation is to divide the image into some areas. Within the same area, the characteristics of the image are similar; and Within different regions, image features vary widely. Image features can be features of the image itself, such as pixel gray levels, edge contours, and textures. Image thresholding is the most commonly used, and also the simplest method of image segmentation. The purpose of image thresholding is to divide the pixel set according to the gray level, and each sub-set obtained forms a region corresponding to the actual scene.The interior of each region has consistent attributes, and the layout of adjacent regions has this. Consistent attributes.

Third, due to the diversity of images in industrial inspection, for each image, various methods must be analyzed and comprehensively considered to achieve the effect. In general, the gray value of the scratched part is darker than the surrounding normal part, that is, the gray value of the scratched part is relatively small; moreover, most of it is on a smooth surface, so the gray change of the entire picture is generally It is very uniform and lacks texture features. Therefore, the detection of scratches generally uses a method based on statistical gray features or threshold segmentation to mark the scratches.

In the traditional product manufacturing process, the surface defect detection of products is generally carried out by manual inspection methods. With the continuous development of science and technology, especially the development of computer technology, computer vision detection technology has appeared. The system designed using this new technology is not affected by harsh environments and subjective factors, and can quickly and accurately detect the quality of products, completing inspection tasks that cannot be done manually.

The products of Shenzhen TEO Technology Co., Ltd. cover industrial and medical machine vision systems and products, mainly including: a full range of industrial cameras, cameras for industrial image measurement, crosshair cameras for laser cutting, image collectors for micro-imaging, ultra-high-definition pathology Microscopic imaging conference system, pathological microscopic image analysis and remote consultation system. The products are widely used in scientific research institutes, hospitals, schools, factories and mining enterprises, cultural relics appraisal units, criminal investigation justice, intelligent transportation and other industries.


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