A typical machine vision system consists of a digital or analogous camera, embedded systems consisting of processors and software, a frame grabber, and lighting. Unlike the traditional, expensive manual laborers that mess up repetitive tasks, waste a lot of time and create bottle-necks in the workflows, machine vision systems get the same job done with formidable accuracy and speed. And the best thing is that these systems are cost-effective and work with top-notch efficiency.
In 2017, MarketWatch cited that the machine vision market valued at USD 6.41 billion in 2017, is expected to reach USD 13.53 billion by 2023, at a CAGR of 13.27% during the forecast period 2018-2023. These statistics are tell-tales that scream the rising prominence of machine vision.
Types of Sensors
Charge-Coupled Device (CCD)
The CCD sensor is a silicon chip that consists of numerous photosensitive sites. The term charge-coupled device refers to how charge packets are transferred from the photosensitive locations to the readout, analogous to a bucket brigade.
Potential wells created by clock pulses facilitate the movement of charge packets around the sensor. While the CCD sensor is itself an analog device, the output is immediately converted into a digital signal using an analog-to-digital converter. Some reasons to adopt CCDs are:
Complementary Metal Oxide Semiconductor (CMOS)
In the CMOS sensor, the charge from a photosensitive pixel is converted into a voltage. The signal is then multiplexed by row and column to multiple on-chip digital-to-analog convertors or DACs. Each photosensitive site is composed of a photodiode and three transistors, which activate the pixel, perform amplification and charge conversion, and multiplexing.
An electronic rolling shutter often accompanies the multiplexing configuration of a CMOS sensor. Some reasons to adopt CMOS are:
Alternative Sensor Materials
Short-wave infrared (SWIR) is a recent advancement in imaging. SWIR wavelengths facilitate the imaging of density variations, even through obstructions such as fog. CCD or CMOS images are not sensitive enough in the infrared range to be useful.
This issue can be resolved by using special Indium Gallium Arsenide (InGaAs) sensors. The InGaAs material has a bandgap that leads to the formation of photocurrent from infrared energy.
2. Sensor size
3. Frame rate and shutter speed
4. Electronic shutter
Since the solid-state sensor is based on the photoelectric effect, it cannot differentiate between colors.
There are two types of CCD color cameras: Single-chip and three-chip.
Single-chip ones use a mosaic optical filter to segregate the incoming light into different colors. These colors are then directed to a different set of pixels. The three-chip alternative, on the other hand, uses a prism to direct different colors to different chips.
Undoubtedly, sensors are the heart of all machine vision cameras. Modern sensors are solid-state silicon chips that convert the incoming photons into digital signals. These signals can further be analyzed, viewed, and transferred. However, understanding the key concepts, characteristics and basic terminology is a prerequisite for selecting the apt camera sensor for your vision system.