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Choosing The Right Sensor For Machine Vision Applications

The traditional battle between CCD and CMOS sensors is almost over, with victory in favour of sensors with CMOS technology. When it comes to vital decisions in designing a machine vision system, we must now turn to a few key sensor parameters which will have a greater influence on the final performance of the system. In this article, we will explore these parameters and analyse what types of vision applications will benefit the most from each of them.

The Influence of Pixel Size

Pixels are the individual elements which capture light to make up an image. The ability of a pixel to convert an incident photon to charge is specified by its quantum efficiency, which will be different for different wavelengths.

In machine vision cameras, pixels are normally between 1.85μm to 9μm and although the pixel size is normally underrated, it can be quite important when choosing the right optics for the application.

Large pixel sizes typically offer better saturation capacities and signal to noise ratios, resulting in better dynamic range. Smaller pixels are good for low noise applications and allow bigger resolutions with smaller sensor sizes, facilitating the choice of optics. Big pixel sizes are often required in applications like astronomy or traffic, while small pixel sizes can be beneficial for biomedical applications.

The Importance of Sensor Size

The sensor is the camera´s active area and its size is important to understand the end system’s field of view. For a fixed focal length, bigger sensors will achieve greater fields of view. However, this doesn’t come for free. Bigger sensor sizes will require supporting optics that don’t degrade the image towards the edges or produce greater distortions.

Difference between Monochrome vs Colour Sensors

This is a common question that many users face when choosing a camera for their application. The big majority of colour sensors use an optical filter on each pixel to separate incoming light into a series of colours. This is commonly known as a Bayer Filter.

Since more pixels are required to recognise colour, these sensors will yield lower effective resolution than their monochrome counterparts. Colour sensors would be appropriate in applications that require colour segmentation or classification. However, monochrome sensors are better for high accuracy applications, such as metrology or barcode scanning.

Difference between Rolling vs Global Shutter Sensors

Industrial cameras are often available with a range of rolling shutter sensors and global shutter sensors.

A global shutter sensor exposes and samples simultaneously. This means that the image acquisition starts and stops at the same time for all the pixels.

However, a rolling shutter sensor exposes and samples sequentially, which means that each line of the image is sampled at a different time, resulting in distorted images when there’s presence of a moving object.

With these differences in mind, rolling shutter sensors are recommended for low budget applications with stationary targets, or targets that move at very low speeds, such as life sciences or metrology applications.

On the opposite side, global shutter sensors are recommended for high-speed applications with medium-to-high-speed moving targets, such as sports analysis, broadcasting, AOI and defect detection on moving conveyors.

All the above information has been carefully detailed in the data sheets of our cameras, available on our website to facilitate the decision when choosing the optimal machine vision camera model for your industrial application.






Machine Vision lets computers read barcodes, data matrix codes, direct part marks, optical character recognition and optical character verification – Learn more about the computer vision technology here

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