What Is The Principle Of 3D Camera Machine Vision Inspection?

With the continuous development of industrial automation, traditional two-dimensional visual inspection systems are no longer able to meet the modern manufacturing industry's demand for high-precision, high-efficiency, and high flexibility inspection. 3D camera machine vision inspection technology has emerged as a key tool in intelligent manufacturing and quality control. So, what is 3D camera machine vision inspection? What is its working principle? This article will provide you with a detailed analysis.
1, Basic concepts of 3D camera machine vision inspection
3D camera machine vision inspection refers to an automated detection method that uses 3D imaging devices (such as 3D cameras) to obtain three-dimensional spatial information of objects, and combines image processing algorithms to detect and analyze the size, shape, position, defects, etc. of objects.
Compared with traditional 2D vision systems, 3D vision can not only obtain planar images of objects, but also their depth information, thereby achieving accurate recognition of complex structures, surfaces, height differences, and other features.
2, The working principle of 3D camera
A 3D camera is the core device for implementing 3D visual inspection, and its working principle mainly relies on the following mainstream technologies:
1. Structured Light
Structured light technology projects specific light patterns (such as stripes or dots) onto the surface of an object, and when the light encounters surface undulations, it undergoes deformation. After capturing these deformed patterns with a camera, the depth information of each pixel is calculated through image processing algorithms to construct a three-dimensional model of the object.
Advantages: High precision, suitable for static or slow speed scenarios
Disadvantages: Sensitive to ambient light, not suitable for high-speed or reflective surface detection
Application: Mobile phone frame size detection, electronic component flatness measurement, etc
2. Time of Flight (ToF)
ToF technology calculates the distance between an object and a camera by emitting infrared light pulses and measuring the time it takes for the light to reflect back to the camera. By quickly scanning the entire field of view, the system can generate a complete depth map.
Advantages: Fast response, suitable for dynamic detection
Disadvantages: Low resolution, accuracy limited by distance
Applications: AGV obstacle avoidance, parcel volume measurement, autonomous driving, etc
3. Stereo Vision
Simulate the principle of human visual perception, use two cameras to capture the same object from different angles, calculate the disparity through image matching algorithms, and thus calculate the three-dimensional coordinates of the object.
Advantages: Simple structure, low cost
Disadvantages: High texture requirements, difficult to match weak texture areas
Applications: Robot grasping, outdoor navigation, object recognition
3, The workflow of 3D visual inspection
A complete 3D visual inspection system typically includes the following steps:
1. Image acquisition
Obtain image data containing depth information through a 3D camera, such as point cloud maps, depth maps, or grayscale maps.
2. Image preprocessing
Perform denoising, filtering, coordinate transformation, and other processing on the raw data to improve the stability and accuracy of subsequent algorithms.
3. Feature extraction and matching
Extract key features from the image, such as edges, contours, and planes, and compare them with standard models or templates to identify defects or deviations.
4. 3D reconstruction and measurement
Using point cloud data to reconstruct a three-dimensional model of an object for size measurement, volume calculation, shape analysis, and other purposes.
5. Defect identification and judgment
Combining machine learning or deep learning algorithms to classify and determine detected anomalies, and output detection results.
4, The advantages of 3D visual inspection
Compared to traditional manual inspection or 2D vision systems, 3D vision inspection has the following significant advantages:
High precision: It can achieve measurement accuracy at the micrometer or even sub millimeter level, meeting the requirements of precision manufacturing.
High adaptability: able to handle complex shapes, reflections, transparency, low contrast, and other 2D difficult to handle scenes.
High efficiency: Automated detection speed is fast, suitable for large-scale production lines.
Non contact: avoids damage to the workpiece and is suitable for fragile or high-value products.
5, Typical application scenarios
3D visual inspection has been widely applied in multiple industries, and the following are some typical scenarios:
Electronic manufacturing: detecting PCB solder joints, chip mounting accuracy, phone shell dimensions, etc.
Automotive components: measure dimensional errors and surface defects of engine cylinder blocks, gears, and brake pads.
Logistics and Warehousing: Automatically measure package volume, identify cargo posture, and guide AGV to avoid obstacles.
Food and Medicine: Testing packaging integrity, bottle cap sealing, and appearance defects of tablets.
6, Future Development Trends
With the continuous progress of artificial intelligence, edge computing and sensor technology, 3D visual inspection is developing towards higher accuracy, faster speed and stronger intelligence:
AI+3D Vision: The application of deep learning algorithms in point cloud processing and defect recognition is becoming increasingly widespread.
Edge computing: deploy image processing algorithms on local devices to achieve millisecond response.
Multi sensor fusion: Combining multiple sensors such as RGB, infrared, and laser to improve detection robustness.
Modularization and Standardization: Promoting the rapid deployment and industrial popularization of 3D vision systems.
7, Conclusion
3D camera machine vision inspection technology is gradually becoming the "smart eye" of industrial automation. It not only improves the accuracy and efficiency of detection, but also provides a solid data foundation for intelligent manufacturing. In the future, with the continuous maturity of technology, 3D vision will demonstrate its powerful application potential in more fields.