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Machine vision surface defect detection
Author:Administrator   Published in:2019-11-08 11:48

China is producing a large number of industrial products every day. It is a big manufacturing country. Users and production enterprises have higher and higher requirements for product quality, not only to meet the use performance, but also to have good surface quality. However, in the process of manufacturing products, the appearance of surface defects is just inevitable. For manufacturing enterprises, the problem of product defects has always been one of the core pain points. If this problem is not solved, it will easily lead to accidents. So how to improve the quality of products and reduce the consumption of raw materials and labor cost has become the core problem faced by the factory in the process of digital and intelligent transformation. Machine vision surface defect detection mainly includes two-dimensional detection and three-dimensional detection. This paper mainly discusses two-dimensional detection of main surface defect detection methods.

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Manual inspection is the traditional method of product surface defect detection. This method has low sampling rate, low accuracy, poor real-time performance, low efficiency, high labor intensity, and is greatly influenced by human experience and subjective factors. However, the inspection method based on machine vision can largely overcome the above disadvantages.

According to the definition of machine vision by the American Association of robotics industry (RIA), "machine vision is a device that automatically receives and processes the image of a real object through optical devices and non-contact sensors to obtain the required information or to control the robot movement".

Machine vision is a non-contact, non-destructive automatic detection technology, which is an effective means to realize the automation, intelligence and precision control of equipment. It has the advantages of safety, reliability, wide spectral response range, long-term work in harsh environment and high production efficiency. The machine vision detection system obtains the surface image of the product through the appropriate light source and image sensor (CCD camera), extracts the feature information of the image by the corresponding image processing algorithm, and then carries out the identification, identification, classification and other operations of the surface defect location, statistics, storage, query and so on according to the feature information;

The basic components of visual surface defect detection system mainly include image acquisition module, image processing module, image analysis module, data management and human-machine interface module.

The image acquisition module is composed of CCD camera, optical lens, light source and its clamping device. Its function is to complete the acquisition of product surface image. Under the illumination of the light source, the product surface is imaged on the camera sensor by the optical lens. The optical signal is first converted into electrical signal, and then into the digital signal that can be processed by the computer. At present, industrial cameras are mainly based on CCD or CMOS (complex metal oxide semiconductor) chips. CCD is the most commonly used image sensor in machine vision.

Light source directly affects the quality of the image, its function is to overcome the interference of ambient light, ensure the stability of the image, and obtain the image with the highest contrast. At present, the commonly used light sources are halogen lamp, fluorescent lamp and led. LED light source has been widely used for its small size, low power consumption, fast response, good monochromatic performance, high reliability, uniform and stable light, easy integration and other advantages.

The lighting system composed of light source can be divided into light field lighting and dark field lighting, structural light lighting and frequency flash lighting according to its illumination method. Light field and dark field mainly describe the position relationship between the camera and the light source. Light field illumination refers to that the camera directly receives the reflected light of the light source on the target, generally the camera and the light source are distributed on the opposite side, which is convenient for installation. Dark field illumination refers to that the camera indirectly receives the scattered light of the light source on the target, generally the camera and the light source are distributed on the same side, which has the advantage of obtaining high contrast image. Structured light illumination is to project grating or line light source on the measured object, and demodulate the 3D information of the measured object according to the distortion caused by them. Frequency flash illumination is to irradiate the high frequency light pulse on the object, and the camera shooting needs to be synchronized with the light source.

Image processing module mainly involves image denoising, image enhancement and restoration, defect detection and target segmentation.

Because the scene environment, CCD image photoelectric conversion, transmission circuit and electronic components will make the image produce noise, which will reduce the quality of the image and have a bad impact on the image processing and analysis, so it is necessary to preprocess the image to remove the noise. The purpose of image enhancement is to purposely emphasize the whole or local characteristics of an image for a given application, to make the original unclear image clear or to emphasize some features of interest, to expand the differences between the features of different objects in the image, to suppress the features of uninterested, to improve image quality, enrich information, and to enhance image interpretation and recognition effect Handling method. Image restoration is a process of reconstruction or restoration of degraded image through computer processing. Image restoration often uses the same method as image enhancement, but the results of image enhancement still need to be verified in the next stage; image restoration attempts to use the prior knowledge of the degradation process to restore the original appearance of the degraded image, such as the elimination of additive noise, the restoration of motion blur, etc. The purpose of image segmentation is to segment the target area in the image for the next step.

Image analysis module mainly involves feature extraction, feature selection and image recognition.

The function of feature extraction is to extract the amount of expression that can describe the characteristics of the target from the image pixels, map the differences between different targets to the low-dimensional feature space, so as to help compress the amount of data and improve the recognition rate. Generally, the features extracted from surface defect detection include texture features, geometric features, color features, transform coefficient features, etc. these multi information fusion feature vectors are used to distinguish reliably different types of defects. Generally, there is redundant information between these features, that is, it can not guarantee that the feature set is optimal, and a good feature set should have simplicity and robustness. Therefore, it is necessary to It is necessary to further select features that are more conducive to classification from feature set, that is, feature selection. Image recognition mainly trains the classifier according to the extracted feature set, so that it can recognize the surface defect types correctly.

The data management and human-machine interface module can display the defect type, position, shape and size on the display immediately, and store, query and count the image.

Machine vision has been widely used in industrial detection, packaging and printing, food industry, aerospace, biomedical engineering, military science and technology, intelligent transportation, character recognition and other fields. With the improvement of economic level, machine vision detection has been paid more and more attention. It can improve the production capacity of qualified products, discard inferior products, reduce waste and save cost.

The above is all about "machine vision surface defect detection", I hope to help you. If you want to know more about machine vision, please pay attention to our TEO technology. In addition, you can call us at any time to contact us when you need this. We will provide you with high-quality products and sincere services. We are looking forward to cooperating with you!

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