Components of a Real-Time Machine Vision System
| By: Jerry Leitz, Director of Field Engineering, Motion Control
Machine vision processes consist of algorithms that review images and extract information, make required decisions, and run necessary inspections in real-time. Communication among machine vision systems is executed by a discrete I/O signal or data passed over a serial connection to a device that logs or uses information. The main components of a real-time machine vision system include image sensors, lighting, communications, vision processing and lenses.
Machine vision systems form images by analyzing the light reflected from an object as opposed to analyzing the object itself. Hence, machine vision lighting involves a lighting source and its placement with respect to the camera and the part. Specific lighting techniques can enhance images to negate some features while enhancing others. Lighting illuminates the parts under inspection to allow their features to stand out so that they are clearly captured by the camera.
The lens captures images and delivers them to the camera’s image sensor. Lenses vary in regards to price and optical quality. As such, the lens used affects the resolution and quality of captured images. Most real-time machine vision system cameras offer two lens types: fixed lenses and interchangeable lenses. Interchangeable lenses are either CS-mounts or C-mounts, and a good extension and lens combination produces high-quality images. Fixed lenses rely on autofocus that can be adjusted mechanically or liquid lenses that can focus on their preferred part automatically. Autofocus lenses are characterized by having fixed view fields from a predetermined distance.
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A camera’s ability to capture high-quality images depends on the camera’s lens and the image sensor. Image sensors rely on the complementary metal oxide semiconductor (CMOS) or charge coupled device (CCD) technologies to turn photons (light) into electrons (electrical signals). Image sensors capture light and convert it into digital images while balancing sensitivity, dynamic range, and noise. The higher the image sensor resolution, the more details and accurate measurements an image will have.
Vision processing entails the extraction of information from a digital image. It can take place externally or internally in a standalone vision processing system. Vision processing consists of different steps that are performed by software. The image is acquired from the sensor, the processing software locates the required features, runs the measurements and compares them to specifications before a decision is made and the final results are communicated.
All machine vision components must connect and coordinate with other machine elements easily and quickly. The connection and coordination are facilitated by the discrete I/O signal or data sent over serial connections to devices that are using information or logging it. Discrete I/O points can be connected to a PLC that uses the information to control an indicator or a work cell.
All of these real-time machine vision components work together to provide accurate specifications. System algorithms ensure that all components communicate to evaluate processes and deliver required solutions in real-time.