Industrial machine vision technology is a technique that uses machines to replace human eyes for measurement and judgment. It converts the captured target into an image signal, processes it to extract features, and controls device actions. It can improve production flexibility and automation, and is applied in hazardous or visually challenging scenarios, enhancing production efficiency and product quality, and facilitating information integration.

System Composition

• light sourceUsed to provide lighting, different types of light sources have differences in price, brightness, stability, and other aspects. When choosing, detection needs should be considered.
• lensThere are multiple classification methods, and their parameters affect the imaging effect. When selecting, factors such as system accuracy and workspace should be comprehensively considered.
• industrial cameraAccording to image sensors, output colors, sensor types, and output signals, they can be classified into different types. When selecting, attention should be paid to system accuracy, speed, and other requirements.
• Image acquisition card: is the interface for image acquisition and processing, responsible for converting analog signals into digital signals, and its parameters and functions affect the quality of image acquisition.

Involving technology

Industrial machine vision is a comprehensive technology field that covers multiple key technologies and components:

Visual algorithm

Industrial machine vision algorithms are a subset of image processing algorithms, which have characteristics such as controllable lighting conditions, prior knowledge of the inspected workpiece, high efficiency, and high reliability for industrial applications. The basic steps of image processing include preprocessing, segmentation, feature extraction, etc. Among them, preprocessing algorithms include filtering, morphological processing, binary processing, and image arithmetic, which are used to enhance images and remove noise; The subsequent steps can achieve functions such as target segmentation, feature calculation, and edge detection. Target recognition and measurement can also be achieved through methods such as template matching and geometric feature matching. In addition, visual system calibration is used to correct image distortions, associate reality with camera scale, and stereo vision can reconstruct three-dimensional geometric information of the scene.

Application field

Industrial machine vision technology is widely used in multiple industries and plays an important role in quality inspection, size measurement, target recognition, and positioning in various industries

• Consumer grade productsFor example, in the processing of consumer electronics products, it can be used for product appearance defect detection.
• Industrial grade productsIn the fields of automobile manufacturing, semiconductor, PCB, SMT, etc., it can perform part inspection, IC character reading, etc.
• BiomedicineSuch as sperm tracking, medical equipment malfunction detection, etc.
• safetyFor example, driver attention detection.
• Logistics and warehousingUsed for identifying and tracking goods, achieving rapid classification, storage, and transportation of goods through automatic recognition of labels, barcodes, and other information.
• Intelligent InstrumentCan detect and identify the status and location of instruments to assist in maintenance and management, such as detecting faults or abnormal situations in medical equipment in the medical field.
• Food and BeverageLike sorting red dates.
• pharmaceuticalDrug quality inspection, etc.

System construction and evaluation

When building the system, it is necessary to select suitable light sources, lenses, and cameras according to the project testing terms, conduct project testing, establish a prototype testing program, and record the test results. When evaluating machine vision projects, the selection of lighting sources, lenses, cameras, and project testing are important considerations. By comprehensively evaluating these aspects, the system can ensure that it meets project requirements.

development trend

• Technological innovation continues to emergeWith the continuous development of technologies such as artificial intelligence and deep learning, machine vision technology is also constantly innovating and advancing. In the future, machine vision systems will become more intelligent and autonomous, able to better adapt to various complex environments and task requirements.
• The application field continues to expandIn addition to traditional manufacturing, electronics, and automotive industries, machine vision technology will gradually penetrate into other industries such as healthcare, agriculture, logistics, and security. Meanwhile, driven by emerging technologies such as AI, autonomous driving, and facial recognition, the market size will continue to maintain a high growth rate.
• Integration and modularizationFuture machine vision systems will be more integrated and modular. Integrated machine vision systems will have stronger functionality and performance; Modular machine vision systems will be more flexible and customizable, capable of rapid deployment and configuration according to user needs.
• The application of 3D machine vision inspection is increasingThe application scope of 3D machine vision inspection is becoming increasingly broad, and its role in improving product quality and production efficiency will be more significant.
• Multi technology integrationWith the integration of machine vision technology with the Internet of Things, big data, cloud computing and other technologies, it will promote the development of industrial machine vision technology towards a more intelligent and automated direction.