6 Core Components Of A Vision System

All vision systems share the same core components. These include essential components and key components that are fundamental to system architecture. They may not be engineered as the discrete modules depicted in this infographic, but they will share the same key parts, functionality, and connectivity.

When making a decision to build or to buy a vision system, it’s important to understand and consider each of these components. The design requirements for these components are interdependent, so the design process usually begins with the selection of an image sensor that best suits the intended application of the system you are developing. The choice of vision hardware, including whether to use commercial off the shelf (COTS) components or custom-built solutions, can significantly impact the system’s performance by affecting flexibility, cost, and reliability.

Introduction to Vision Systems

A vision system is an integrated solution that enables machines to interpret and act upon visual data from their surroundings. At the heart of every machine vision system is the image sensor, which captures light and transforms it into electrical signals. These signals are then processed by the vision system to extract relevant information, supporting tasks such as quality control, process control, and robot guidance. Proper lighting is crucial for optimal performance, as it ensures the captured images are clear and accurate, directly impacting the system’s ability to analyze visual data. Machine vision systems are widely used across industries, providing the intelligence needed for automated inspection, measurement, and decision-making. By leveraging computer vision technologies, these systems can deliver consistent, high-speed analysis of images, making them essential for modern manufacturing and automation environments.

IMAGE SENSOR AND IMAGE ACQUISITION

The sensor you choose will impact almost every other design choice you make as you build your system. The image sensor provides the core functionality for the vision system, and will establish the requirements for the optics design, data transport, and power consumption.

Some 3D sensing technologies use multiple image sensors mounted side-by-side to create a stereographic image. Advanced vision systems often use multiple cameras to capture synchronized or multi-channel image data, enabling more comprehensive analysis and flexibility in machine vision applications.

There are a range of factors to consider when selecting an image sensor, starting the with the required operating spectrum of the sensor:

• Is your vision system intended for use in visible light, ultraviolet, or short-wave infrared?
• Will your vision system be operating under controlled conditions or outside?
• Will your vision system be required to operate in low light conditions?

The camera captures images by recording the reflected light from the target object. The ability to capture images and produce clear images depends on the light intensity and the quality of the light source, such as LED lights and lighting modules, which are essential for proper illumination. The sensor converts the incoming light into a digital signal, which is then processed into a digital image or acquired images for further analysis by the system.

In addition to your required image resolution, you must consider the required image acquisition speed and frame rate, and whether your application require a global shutter – to capture high-speed motion – or a rolling shutter sensor for lower cost and higher available resolutions. The choice of camera lens and its focal length are also critical, as they determine how light is directed onto the sensor and affect overall image quality. Data transport between the sensor and processing units often relies on frame grabbers or a frame grabber for high-speed, reliable transfer of image data, especially in professional setups. Processing time is another important factor, as a faster system can reduce delays in image analysis and improve responsiveness.

If your answers to these questions look like a lot of other people’s answers, and your sensor selection is fairly typical of other cameras and camera modules, you may choose to look for an off-the-shelf solution for your vision system. These solutions often utilize PC based systems, machine vision software, and an image processing system to handle and analyze sensor output for a wide range of machine vision applications. Connectivity is also a key consideration, with the communication interface playing an important role in linking sensors to other system components. However, if you have very specific requirements, the better choice might be to build at least part of your solution yourself.

SENSOR MODULE

The sensor module is a key component of any vision system. It not only acts as a substrate for the sensor and lens mount, but must also provide access to the data lines on the sensor, and a physical connection to an appropriate sensor adapter for the data communications protocol employed in your vision system to get the raw image data from the image sensor to an image processor or image processor adapter. The communication interface is a critical aspect of sensor module design, enabling reliable data transfer between the sensor and other components within the vision hardware.

Sensor module are designed so engineers can quickly build a prototype and a proof of concept. Later in the product development cycle, you might choose to develop your own PCB that includes only the features you need, or you might choose to integrate the sensor module into your design.

While the sensor module in your final design may not be a discreet PCB as shown here, all vision systems will require the same core functionality to “talk” to the sensor. Because of the high density of the data lines connecting to the sensor, and the requirement for a multi-layer PCB design, this component can present a high engineering cost to develop from scratch, so an off-the-shelf sensor module may be a good choice – at least during prototyping. Commercial off the shelf sensor modules are widely available as part of the broader vision hardware ecosystem, offering flexibility and rapid integration for a variety of system requirements.

OPTICS

Choosing the right lens and lens mount for your choice of sensor is essential to providing the right performance for your vision system. The camera lens plays a crucial role by focusing the reflected light from the target object onto the sensor, and the focal length of the lens determines the field of view and image characteristics for your application. The required lens is determined in part by the physical size of the image sensor, (and what the resulting image circle must be), and in part by the working distance of the vision system.

For example, webcams, that are typically used at a very close distance to the subject will require a wide-angle lens with a short minimum focusing distance, while security cameras are typically used at a longer working distance, and may require a zoom capability. The type and size of the required lens will determine the type of lens mount required.

Some specialized applications will dictate your choice of optics. For example, if you are using a short-wave infrared (SWIR) sensor, you are limited to optics designed for the infrared spectrum, (ordinary glass elements absorb infrared light).

Your choice of lens will determine the type of lens mount required for your camera. The most common types are mounts for screw-mount M12 lenses and mounts for C and CS-mount lenses. There are other types of mounts for large lenses, but these are less typically used.

M12, C, and CS mounts are all screw-type mounts, and differ primarily in diameter, (12mm for M12 lenses as opposed to 25.4mm for C / CS lenses) and in the distance from the flange to the image plate, (sensor surface).

OPTICAL MODULE

Optical Modules offer an easy way to prototype and develop a vision system, and can be incorporated into the final product.

An optical module is a matched combination of a sensor, sensor module and optics that are all compatible and can be used for a specified range of working distances. The lens and lens mount are aligned with the sensor and adjusted for focus during manufacture.

Depending on the system requirements, the optical module can also include a Sensor Adapter module or a Processor Board Adapter. Sourcing an optical module can accelerate the development of a vision system.

SENSOR MODULE ADAPTER

Some vision systems may require a sensor module adapter.

A sensor adapter provides transport for sensor data using a variety of communications protocols, and generally provides a clock for system timing. In high-speed and real-time image acquisition setups, frame grabbers are often used as essential hardware components to interface with the sensor adapter, while a frame grabber installed in the computer acquires image data from the camera and transmits it for processing. The communication interface is a key feature that enables connectivity between the sensor adapter and other system components. Sensor adapters can take the data-stream from the sensor and adapt it for a variety of data transport protocols, converting the sensor output into a digital signal for further processing.

Some common data transport protocols include the mobile industry processor interface (MIPI) and MIPI cameral serial interface 2 and 3 (CSI-2 / CSI-3); gigabit multimedia serial link protocol (GMSL); and is Sony’s SLVS-EC (scalable low-voltage signaling [with] embedded clock).

Your choice of data transport protocol, and your need for a sensor module adapter will largely be determined by the application you are building your vision system for, as well as the performance requirements of the system. For example, the GMSL protocol is often used for automotive applications like rear view back-up cameras, since it allows the sensor module to communicate with the image processor over a coaxial cable up to 15m long.

PROCESSOR BOARD ADAPTER

An image processor board adapter can help speed development of a vision system by communicating directly with a range of embedded computers, like the NVIDIA Jetson Xavier. These adapters can also be used in pc based systems to support more complex machine vision applications and machine vision solutions, especially in industrial automation and quality control.

An image processor adapter may not be part of the final production version of your vision system, but they are invaluable for prototyping and engineering vision systems. In these setups, machine vision software and the image processing system work together to analyze and interpret image data, enabling accurate inspection and measurement.

An image processor adapter allows you to connect the optical components of your vision system to a small board computer like the Raspberry Pi, or an embedded computer like the NVIDIA Jetson series, an image processor adapter is an invaluable off-the-shelf component that can simplify your task.

Image Processor Adapters provide a variety of inputs for different data communications protocols, They’re generally designed to talk to a specific platform, whether it’s an embedded computer like the NVIDIA Jetson Orin, or a field-programmable gate array (FPGA) like the Xilinx Kintex.

Image Processing

Image processing is a foundational element of machine vision systems, involving the manipulation and analysis of digital images to extract relevant information for specific tasks. Techniques such as image filtering, thresholding, and feature extraction are employed to enhance image quality, reduce noise, and highlight important features within the image. These processes are essential for applications like defect detection, object identification, and character recognition, where accuracy and reliability are paramount. The choice of image processing methods depends on factors such as the type of image sensor used, prevailing lighting conditions, and the desired outcome. By tailoring image processing algorithms to the needs of the application, vision systems can deliver precise and actionable results across a wide range of industrial and commercial settings.