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A 3D machine vision camera is an optical device used in industrial automation to capture and process three-dimensional images of objects or scenes. By mapping scenes in 3D, these cameras can handle changes in the environment and variations in the objects being analyzed. They are ideal for inspection, process control, measurement, and robot guidance applications that require high precision.
In-Sight L38
The In-Sight L38 is a next-generation 3D vision system that allows manufacturers to detect subtle features and measure them with high accuracy. The first-ever 3D vision system with embedded AI, the In-Sight L38 takes 3D applications beyond measurements to enable new types of inspections.
There are two main types of 3D cameras: area scan and line scan. The difference between the two methods is how the image is acquired.
Area scan cameras capture an image in a single frame. These cameras are suited for machine vision applications, where the objects are stationary, fixed in size, and relatively uniform in shape. By contrast, line scan cameras build images line-by-line and require motion to build the image. This makes them ideal for inspecting cylindrical parts and continuous materials, like paper, wood, and rubber.
In addition to line scan and area scan cameras, laser profilers are another technology used to solve 3D machine vision applications. They inspect height and other 3D profile data by capturing an object’s shape from above. Laser profilers can operate without external lighting and generate reliable profile measurements without being affected by color differences, patterns, and other characteristics of the target object.
Area scan cameras (left) capture images in a single frame, while line scan cameras (right) build images line-by-line.
What’s the difference between 2D and 3D vision systems?
With 2D machine vision, a two-dimensional map (X, Y) of reflected intensity is captured and processed. Processing consists of comparing variations in intensity or contrast. For this reason, 2D vision systems need highly controlled environments with standard viewpoints and lighting that creates high contrast and eliminates shadows. These systems are typically used for applications like defect detection, optical character recognition (OCR), and assembly verification.
3D machine vision captures the depth of a target object to generate a three-dimensional map (X, Y, Z), or point cloud, for analysis. The point cloud offers precise coordinates where the position of every pixel in space is known. This makes 3D vision useful for tasks where shape information is critical. 3D machine vision works well with objects that can vary in size and shape, like food, welds, metals, and more.
2D images (left) show variations in contrast, while 3D images (right) capture a three-dimensional map of an object.
What are the advantages of 3D machine vision systems?
By adding an extra dimension to image analysis, manufacturers can automate applications once considered too challenging for traditional automation, while gaining all the benefits and features of 2D vision. These benefits include:
Inspection and quality control
3D machine vision is widely used in manufacturing for quality control. It inspects the surface of materials for defects such as dents, scratches, or inconsistencies and assesses the severity of those defects. 3D vision systems also ensure proper assembly and verify dimensions of target objects in real time to automate production processes, significantly reducing errors and increasing efficiency.
Gauging and measurement
Gauging applications in 3D vision technology check the tolerances of manufactured parts, ensuring that they fall within acceptable limits. 3D vision systems can also be used to analyze complex components, like those used in electronics or precision engineering. For those applications, they assess and verify complex geometries that are difficult to measure with traditional methods.
Robotic guidance
3D machine vision cameras help robots “see.” By providing real-time 3D perception of the environment, these cameras enable robots to navigate safely, interact with objects, and execute complex tasks autonomously. This synergy between machine vision and robotics transforms industries by reducing manual intervention and minimizing human errors.
Object recognition and location
3D object location assists in identifying parts on a production line, ensuring they are correctly oriented and positioned for the next stage of the manufacturing process. In assembly operations, 3D vision systems ensure that parts are properly aligned before they are joined or assembled. This helps in reducing errors and increasing the efficiency of the process.
Logistics and warehouse automation
3D machine vision cameras accurately measure the dimensions of packages and determine their volume. This data allows logistics providers to improve the efficiency of their sorting operations and optimizes the utilization of storage space, leading to streamlined warehousing and improved inventory management.
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