How do I sort through all the new industrial camera image sensors to make a decision? Download the sensor cheat sheet!

The latest CMOS image sensor technology from Sony and ON-SEMI have continued to expand the industrial camera market. Sony has now reached its 3rd Generation Pregius sensors in addition to adding the low light performer, Starvis sensor. ON-SEMI has also continued with higher resolutions and has the next generation in the works.

Given all these new sensors, we are often asked, “What is the best image sensor and camera for my application”?

Although there are many considerations in general on selecting a camera (i.e Interface, Size, Color vs Mono etc), its best to start with the characteristics of image sensor and performance. Knowing the answers to questions relating to amount of available light, dynamic range requirements, wavelengths involved, and the type of application, the right sensor can start to be identified. From there, we can select a camera with the appropriate sensor fitting other requirements such as interface, frame rate, bit depths etc.

In order to help pick a sensor, its extremely important to have the image sensor data that can be found on the EMVA1288 data sheets. We have continued compiling this data into a “cheat sheet” along with required lens recommendations and comments how how some sensors relate to each other and older CCD sensors for your download.

The data shows us that not all industrial camera image sensors are created equally! Within the Sony Pregius sensors, there is 1st and 2nd Generation sensors both having unique characteristics. The 1st Generation provided great pixel well depth and dynamic range with 5.86um pixels. The 2nd generation came along with smaller 3.45um pixels, improved sensitivity and lower noise, but less well depth. The next generation will have the best of both worlds.. more to come on that front.

Using this data as an example, if we had an application with a “fixed” amount of light and wanted a relatively bright image (given a fixed aperture and just considering sensor characteristics), what sensor is best? Answer: We’d probably look at Model A with a smaller well depth as the pixel will start to saturate faster than Model C. Or possibly we have a very small amount of light? We’d start looking at absolute (abs) sensitivity which tells us the smaller # of photon’s, 1.1 in this case, starts to provide a useful signal.

Example comparisons:

Don’t let yourself get frustrated trying to figure this out on your own! 1st Vision’s engineers have combined experience in the machine vision and imaging market of over 100 years! Our team can help explain the various technical terms mentioned in this post and help in selecting the best image sensor and camera for an application.

Related Blog posts

What are the attributes to consider when selecting a camera and its performance?

IMX174 vs Starvis IMX290 – Battle of the 2 Megapixel Image sensors – Sony Pregius IMX174 vs Starvis IMX290

IMX174 vs CMOSIS CMV2000 – CMOS battle between 2MP Sony Pregius and CMOSIS

IMX250 vs ICX 625 – 5MP’s sensor battle between Sony’s older CCD vs new CMOS model

January 3, 2018March 2, 2023

What are global shutters and rolling shutters in machine vision cameras? How can we use lower cost rolling shutter cameras?

We often are asked the question, “What is the difference between a global and rolling shutter image sensor in machine vision cameras? ” Although they both take nice pictures, they are very different image sensors with pro’s and con’s of each. In the end, rolling shutter image sensors cost less, but are not always recommended for moving objects.

In this blog post, we will explain the differences between global and rolling shutter sensors used in machine vision cameras. Additionally, we highlight how to use a rolling shutter camera capable of “Global Reset” providing low cost solutions for some applications with moving objects.

First, let’s explain the differences between rolling shutter vs global shutter image sensors in machine vision cameras.

Global Shutter: Image sensors with a global shutter allow all of the pixels to accumulate a charge with the exposure starting and ending at the same time. At the end of the exposure time the charge is read out simultaneously. In turn, the image has no motion blur on moving objects. This is given the exposure is short enough to stop pixel blur which is a topic for another blog.

Rolling shutter: Image sensors with a rolling shutter do NOT expose all the pixels at the same time. Alternatively, they expose the pixels by row with each row having a different start and end time frame. The top row of the pixel array is the first to expose, reading out the pixel data followed by the 2nd, 3rd & 4th row and so on. Each of the rows start and end point have a delay as the sensor is fully read out. The result of this on moving objects is a skewed image

What are the Pro’s and Con’s of each type of shutter?

Global Shutter:
Pro: Freeze Frame images with no blur on moving objects.

Con: Global shutter sensors require more complicated circuit architecture, thus limiting the pixel density for a given physical size. In turn, sensors with a global shutter will have a larger image format driving up lens cost. The complicated circuits also drive up the overall camera cost and will be more expensive vs a rolling shutter sensor.

Rolling Shutter:
Pro: Rolling shutter sensors have a simpler design with smaller pixels, allowing higher resolution in a smaller image format allowing use of lower cost lenses. The simpler pixel design results in lower camera costs!.. For example, Dalsa’s 18MP Nano for < $600!

Con: Image distortion occurs due to the row by row integration and offset on moving objects. Smaller pixels may also require a higher quality lens which is commonly gauged by the lens Modular Transfer Function (MTF). This is really dependent upon your application and can be discussed with a sales engineer. In turn, there maybe a small trade off to consider.

Is there a way to use a lower cost rolling shutter camera on moving objects? Absolutely using a Global Reset mode found in various image sensors.

Using a rolling shutter capable of a “Global Reset” such as the AR1820HS found in the 18MP Teledyne Dalsa Nano C4900 camera will eliminate the image distortion.

A typical rolling shutter image sensor as described above exposes sensor rows separately with a delay as depicted below.

Using a rolling shutter with global reset mode, all rows start integrating at the same time as shown below eliminating the image distortion. It is highly recommended however to use a dedicated strobe and sync with the start of image acquisition. A gradient in the image brightness from top to bottom maybe seen if not with some pixel blur due to longer row exposure

A great camera to consider is the 18MP Teledyne Dalsa Nano C4900 camera. This camera features the ON-SEMI AR1820HS sensor with this capability. With a price point of < $600, this makes it one of the lowest cost cameras per pixel on the market.

1st Vision has over 100 years of combined experience and can help you with camera, lens and other peripheral recommendations. If you have questions regarding the various sensor shutters, please do not hesitate to contact us!

Be sure to read our related blog posts:

What is a lens optical format? Can I use any machine vision camera with any format? NOT!

Demystifying Lens performance specifications – MTF

November 29, 2017November 30, 2017

Machine vision camera and lens selection tools including educational resources

1stvision industrial imaging components — Click on this picture to visit the new site now!

1stVision is making it easier in selecting industrial imaging components! We have introduced new machine vision camera and lens selector tools in our new website in addition to our educational resources.

5 ways to help in your industrial imaging selection are below:

Industrial machine vision camera selector: Sort by manufacturer, interface, resolution, image sensor and image format to name a few.
Machine Vision lens selector: Sort by manufacturer, focal length, format size, and lens quality
Technical Blog: Posts are published monthly with educational content on cameras, image sensors, lenses along with technical primers and white papers. The blog is categorized and allows you to search by a topic.
Knowledge Base: This section contains technical articles on cameras, lenses, interfaces, vision standards and several other topics.

Watch our short video showing the key features in helping select cameras and lenses

Our combined staff has over 100 years of experience in the industrial imaging market! We are well versed in the technical details, down to the camera sensor level and can help ensure the components you select are the best for your application.

November 29, 2017July 25, 2022

How to get greater resolution from your color sensor using a low cost 18 MP IDS camera

IDS UI-3590 camera — IDS UI-3590CP camera

The AR1820HS Image sensor 18 mega pixel sensor in the IDS Imaging IDS Imaging UI-3590 camera models was launched by the sensor manufacturer ON Semiconductor as a pure color sensor. Like all color sensors, the Bayer filter means that you get color images with effectively only around a quarter of the nominal sensor resolution, as the color information for each pixel is obtained from four neighbors

To use each individual pixel, however, it is not sufficient to operate the sensor in RAW data format (without Bayer interpolation). Operating in a raw format results in a different brightness perception of the individual pixels and NOT a usable image.

This technical tip will show you how to use the color sensor as a “pure” mono sensor by appropriate parameter settings and the use of suitable light sources, in order to obtain a significantly higher resolution.

Applications which require a color image and precision will benefit from this camera and method.. and all for less than $600 with the IDS UI-3590LE camera

Background

Bayer Pattern — Arrangement of colour filters in the Bayer matrix

The principle of digital image sensors such as the 18 MP ON Semiconductor AR1820HS means that they acquire only brightness, but not color information.

As a result, a color filter is applied to each pixel during manufacture of the color sensors. This is known as the Bayer matrix.

Of each four pixels, two pixels are given a green color filter, one pixel a red filter and one pixel a blue color filter. This color distribution corresponds to the perception of the human eye and is referred to as the Bayer matrix.

RGB Filter — The RGB filter layers only transmit light with
a particular wavelength

A pixel depicts only the information for one color.

To obtain the complete RGB values for each pixel, the missing primary colors are interpolated from four neighboring pixels using appropriate algorithms. This color interpolation assumes that there are only slight color differences between two adjacent pixels of the same color. Strictly speaking, a sensor with Bayer matrix therefore has only a quarter of the native sensor resolution

Sensor mono mode

Although the Bayer matrix cannot simply be rendered invisible for mono mode, the following two solutions show how you can achieve the desired result depending on the type of application.

1) For “grey scenes” (i.e. dark pin on a white background)

If the 18 MP color sensor is to be used in mono mode for achromatic scenes, note that a broad band light source (white light) must still be used. This is because of the sensor’s Bayer matrix. With this sensor, monochromatic (single color) light would have resulted in the individual pixels transmitting no or less information depending on the wavelength of the light, due to the RGB filter layers used (see Figure 2). This can result in a different brightness perception for the individual pixels. In this case, the RGB enhancement must be calibrated separately for R, G, and B. As a result, you then obtain an identical brightness perception for all pixels as with a mono sensor.

IDS Imaging — Without calibration of the RGB enhancement, the Bayer matrix is clearly visible (left).
After RGB calibration (see RGB histogram, right) there is a homo-geneous brightness perception as with a mono sensor

Note: This RGB calibration is only valid for this specific light source and a “grey” scene. If the light source (wavelength) changes, the RGB enhancement factors have to be re-adjusted.

Contact 1stVision to obtain instructions on switching the Bayer matrix to “invisible” using the uEye Cockpit:2) For “color or grey scenes”

If you work with color scenes in your application, the brightness sensitivity of the individual Bayer pixels constantly changes with the variation in color components. There is also a way to achieve genuine mono mode in this situation. The solution lies in the color spectrum of the 18 MP ON Semiconductor AR1820HS.

Above a wavelength of around 900 nm the color filters for the individual pixels have similar spectral properties. Beyond this threshold, all pixels on the sensor respond practically identically to incident light again – exactly as with a dedicated mono sensor. This means that the Bayer matrix can also be made invisible using this method, both for color and also for grey scenes

AR1820HS Spectrum — The colour spectrum of the AR1820HS shows similar spectral proper-ties of the colour filters above 900 nm

In order to be able to use this spectral property of the sensor as described, you must observe the following:

Ensure defined lighting conditions, i.e. seal off light with other wavelengths shorter than 900 nm as far as possible.
Order your uEye camera with AR1820HS sensor specifically with GL filter (glass). The HQ filter normally ordered with this sensor would block out the long-wave light. By contrast, the GL filter allows light beyond 900 nm to pass with high transmission. The highest possible signal strength thus arrives at the sensor.

Full Information on the IDS Imaging UI-3590LE and UI-3590CP cameras can be found below

IDS-UI-3590LE – 18MP camera, LE version

IDS-UI-3590CP – 18MP camera, CP version

1stVision has over 100 years of industrial imaging experience! Contact us to help select the best camera and lenses for your applications.