Typically, the selection of computer vision system components starts with the camera that will meet all the requirements of the task. In this article, analog cameras are not considered due to their lower image quality.

LUCID’s range of machine vision cameras
There is quite a common misconception that using simple and cheap IP or WEB cameras will solve industrial machine vision tasks.
In fact, there are a number of requirements to the cameras of machine vision in any production:
Reliability, build quality, high fault tolerance
High image quality
High sensor sensitivity
Digital lines for connecting external devices
Industry interfaces
SDK – a development tool for various programming languages
Industrial design, water and dust proof, vibration resistance, high temperature range

Network, WEB or machine vision camera?

Image processing cameras are divided into machine vision, network (IP) and WEB-cameras. The main differences are shown in the table below:

If we are talking about solving optical inspection tasks, image processing with specialized software and in general about obtaining reliable image data, it is necessary to use machine vision cameras. Exactly they allow getting quality uncompressed image, necessary for correct work of algorithms of computer vision (cv – computer vision). It is the absence of compression that guarantees full information about the object and distinguishes machine vision cameras from IP and WEB cameras.

But you do not always need all this extensive (and resource-intensive) information – if you do not need high accuracy, and you just need video or images for human surveillance is to pay attention to more budget network (IP) cameras. Web-cameras are usually used for educational purposes to study computer vision at home and in the lab.

Machine vision cameras, on the other hand, are usually used for various tasks in industry, medicine and life sciences, traffic, as well as high-quality video surveillance. A distinction is made between matrix (2D), line (1D), and three-dimensional (3D) cameras.

Matrix cameras

Equipped with a rectangular sensor, which is an array of pixel values. The image is acquired in a single operation.
Linear cameras

Unlike matrix cameras, they have a sensor that contains just one, two, or less often several rows of pixels. Image data is captured line by line, after which the complete image is reconstructed from the individual lines during the processing stage.
They are used everywhere for quality control of products during their movement – sometimes at very high speed (line scanning frequency can reach up to 80 kHz). Line cameras are often used to inspect coiled material (rolled metal, paper, veneer) or products moving on a conveyor belt.
Specialized 3D cameras

These cameras form a three-dimensional point cloud (3D object model) and are used when it is necessary to “see” the shape of the object. Widely used in ITS, as well as for robot control.
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Smart cameras.

These all-in-one devices have an on-board calculator for on-the-fly image processing. Generally more expensive, less flexible, and generally have worse performance than conventional machine vision cameras + separate calculators. Good for simple tasks where specialized software is not required. Algorithms are usually compiled with the help of constructors based on ready-made templates.
Thus, the answer to the question of what type of camera to choose depends on the application of the camera and the requirements for it.

Two types of sensors can be used in machine vision cameras: CCD and CMOS. They differ both in their design and in the way they operate. In order to select the optimal sensor, it is necessary to first determine the desired range of applications. For example, a CCD sensor will not allow you to use infrared vision, which is necessary if you need to make heat maps of objects.

The advantages of CCD over CMOS are high light sensitivity, better color reproduction, low noise and high dynamic sensitivity. The disadvantages are the complex principle of signal reading, high power consumption and expensive production.

Among the advantages of CMOS (CMOS) sensors are high speed, low power consumption, as well as cheaper and simpler production. The disadvantages are low light sensitivity, pixel fill factor and dynamic sensitivity, as well as high noise levels.

The most common CMOS matrices are from Sony, STARVIS and PREGIUS generations 1-4.