Learn about the new 5GigE camera interface

Machine vision interfaces have continued to evolve over the years increasing data throughput and cable lengths. Commonly used interfaces are GigE and USB3. However, 5GigE is an interface now gaining attention in the industrial imaging / machine vision market with some nice advantages.

We will outline the benefits of 5GigE, but first, lets give a brief overview of the commonly used camera interfaces, with their pluses and minuses:

GigE / GigE Vision

110 MB/s of sustainable throughput. In real world terms, a HD, 2MP camera can get 50-55 fps in 8 bit mono or 8 bit color mode. Note, this isn’t real HD, since you need 60 FPS.
Data cable lengths up to 100m using regular CAT 5e/6 cable.
Easy to put multiple cameras on a system.

USB 3 / USB3 Vision

420 MB/s of data throughput. A HD 2MP camera can run 60 fps in 8 bit mono or color and can also run RGB at 60 FPS no problem. With the higher throughput, a 5MP camera can achieve 85 fps in 8 bit mode.
Data cables up to 5 meters and up to 20 meters with active cables. However, active cables can be quite costly, adding up to $200 in cost.
Not as easy as GigE to put multiple cameras on a system, and gets harder with each additional camera, especially if you have limited USB3 controllers.

As a note, there is no cost difference when using cameras with the same sensor from the same manufacturer with USB or GigE! They will cost about the same with no premium for one interface over the other.

What are the limitations of GigE and USB3 now solved by 5GigE?

USB3 is limited in cable length, so going faster than GigE is great, but you can not have long cable lengths.
GigE has cable lengths up to 100 meters, but is limited to ~ 110MB/s of data, so you do not have the high frame rates as in a USB3 camera.
USB3 in 4+ camera systems is not as stable as GigE AND you’re still limited on cable lengths.

Wait! – What about 10GigE?

Up until now, 10G was the next interface. However, the jump to 10G has quite a few limitations as outlined below.

Heat generation is significant, so cameras are large and not in the smaller 29 x 29mm cube form factor.
Not a lot of demand for very high speed 10G, so not a lot of sensors being offered
Minimal number of manufacturers for 10G, higher cost.
Special cabling, either optical or high quality cat 7.

What we have found is that there are several types of applications for 10G cameras and are as follows

Applications where you need 10G of speed of course (high resolution + fast frame rates)
Require greater than 110MB/s of data and need long cable lengths.
Where there is the required combination of 110MB/s for high frame rates, multiple cameras and long cable lengths, 10G is a perfect solution.

We have seen that the need for higher bandwidth + long cable lengths is more prominent vs. the real need for 10GigE!

Introducing 5GigE that provides increased bandwidth, long cable lengths at reasonable prices! or N Base T.

5GigE (also known as N Base T) has become a new standard for industrial, machine vision cameras.

In the general compute world, a much much larger market than vision, there has also been a need to go faster than GigE. However, the issue of replacing the existing cabling is the major issue preventing this. If you think of a big box store, say a Home Depot for instance, the amount of cabling is huge. Ripping that out and rewiring far exceeds the cost of the equipment to use it!

5G was made to go faster, but use existing cabling. Regular cat6e cable can be used, and 5G is a subset of 10G, so all switches etc. can be kept in service.

5G gives users in the vision market USB3 speeds, but with ALL of the regular GigE features, at a very small premium!

1st Vision’s sales engineers have over 100 years of combined experience to assist in your camera selection. With a large portfolio of lenses, cables, NIC card and industrial computers, we can provide a full vision solution!

July 18, 2018September 5, 2018

Dalsa Nano M2450 polarized camera: Resolving defects that are undetectable with traditional imaging!

The first Genie Nano camera model with a quad-polarizer filter using the Sony Pregius IMX250-MZR 5.1MP monochrome image sensor is now available. The Teledyne Dalsa Nano M2450 camera incorporates the nanowire polarizer filter allowing detection of both the angle and amount of polarized light.

What problems can the Nano M2450 polarized camera solve?

Polarized filtering can reduce the effects of reflections and glare from multiple directions and reveal otherwise undetectable features in the target scene. Polarization enables detection of stress, birefringence, through-reflection and glare from surfaces like glass, plastic, and metal. Sony’s newest image sensor, with its pixel-level polarizer structure, enables the detection of both the amount and angle of polarized light across a scene.

Four different angled polarizers (90°, 45°, 135° and 0°) are positioned on each pixel, and every block of four pixels comprises a calculation unit.

How does polarization work? Theory of operation

Polarization direction is defined as the electrical direction. Light, with its electrical field oscillating perpendicular to the nano wire grid, passes through the filter while that in the parallel direction is rejected.

For Polarized light, only the portion of the light vector perpendicular to the angle of the nanowire filter grid passes.

For example, with a wire-grid polarizer filter at 90 deg. to the maximum transmission is for polarized light at an angle of 0 deg.

The polarizer filter is placed directly on the sensor’s pixel array, beneath the micro-lens array. This design, compared to polarize filters on top of the micro lens array reduced the possibility of light at a polarized angle being misdirected into adjacent pixels (cross talk) and incorrectly detected at the wrong angle.

The Genie Nano’s polarizer filter on the camera sensor is a 2 x 2 pattern, with each pixel having a nanowire polarizer filter with different angles (90, 45, 135 and 0 degree’s)

The image output pattern of the monochrome camera is arranged in 2 x 2 pixel block as follows:

That is, the first line output is an alternating sequence of pixels 0 & 35 degrees, with the following line of 45 and 90 degrees.

Given the proportion of light available through these four filters, any angle of polarized light can be calculated. Any given state of polarization can be composed by two linearly polarized waves in perpendicular directions. The state of polarization is determined by the relative amplitude and difference in phase between the two component waves.

Calculations on the 2×2 filter blocks result in a single pixel for each polarizer filter angle, therefore the resulting image is one fourth the original image resolution. For example, with an original image of 2464×2056, the resulting image is 1232×1028 (original buffer width/2 and original buffer height/2) for a single polarizing angle.

Teledyne Dalsa offers a Polarization demo user interface making it easy to test the polarization techniques for various applications. This includes the ability to see the results of various processing algorithms with the summed images.

Dalsa Polarization demo — As part of the demo program, images can be displayed with pseudo-color mapping

In summary, the new Dalsa Nano M2450 polarized camera can help resolve defects not detected by traditional imaging! Contact 1st Vision to arrange a camera demo in which we will provide the demo polarization software as well or discuss your application. Or click HERE to request a quote

Need line scan? – With the addition of the Genie Nano polarized model, Teledyne DALSA is the first company to offer polarization for both area and line scan (Piranha™4 polarization) cameras

Related Posts

Dalsa line scan polarization camera makes invisible visible!

Teledyne Dalsa TurboDrive 2.0 breaks past GigE limits now with 6 levels of compression

April 25, 2018April 26, 2018

3-CMOS machine vision cameras bring color fidelity to the market at half the price as previous models

Single sensor machine vision cameras use a mosaic filter placed on the sensor to create color images. This is also called a ‘Bayer’ filter, named after the person who invented it. However, color images from this filter lose resolution and color fidelity compared to ‘true’ color images. Spatial resolution is lost due to interpolation, while the Bayer filter pattern reduces true color representation, sensitivity and dynamic range. To overcome these issues, multi-sensor (3-CCD / 3-CMOS) machine vision cameras can be used.

Typically, machine vision 3-CCD cameras were high cost, until now with CMOS sensors becoming the leading image sensor technology. Now, machine vision 3-CMOS machine cameras provide major benefits over Bayer cameras and at more attractive entrance cost.

CMOS sensor technology has lowered the price of 3 image sensor cameras by 50% providing a better alternative to Bayer color cameras for many applications. JAI’s Apex Series 3-CMOS cameras are the game changer for demanding color applications.

Watch this video to learn more about 3-CCD/3-CMOS cameras

Machine Vision 3-CMOS cameras Vs Bayer cameras provide major benefits for color applications

Better color precision – Accurate RGB values are obtained for each pixel so there is no interpolation/estimation of colors as found in Bayer cameras. This can be critical for paint/ink matching, printing inspection systems, digital pathology, or other applications where color values must be extremely accurate.

Better spatial resolution – The Bayer interpolation process also tends to blend edges and small details. While this can be pleasing to the eye, it can make spatial measurements or bar code reading imprecise or error prone, causing the use of more expensive high resolution Bayer cameras or requiring a second monochrome camera for imaging these details

Higher sensitivity – The prism glass in the AP-3200T-USB and associated cameras, has better light transmission properties than the polymer filters in a standard Bayer sensor. This enables more light to reach the pixels for better overall sensitivity and lower lighting requirements.

Lower noise, higher dynamic range – White balancing on a JAI prism camera can be done on individual channels with shutter adjustments instead of adding gain to the image. This results in lower noise and higher usable dynamic range.

What about “improved” Bayer capabilities like 5×5 interpolation?

Several camera manufacturers claim vastly improved capabilities for color imaging, including 5×5 de-Bayering, color-anti-aliasing, denoising
and improved sharpness. But consider the following: 5×5 interpolation
means you are using an even larger area within the image to estimate each pixel’s color value. So while this can do a better job of “smoothing” color transitions to the eye, it can actually result in less-precise color values for image processing, especially where color variation is high.

This is illustrated in the following images, under identical conditions, by a camera with 5 x 5 debayering and a JAI Apex 3-CMOS camera. The CIE L*a*b* reference chart provides a set of exact color values when expected under specified lighting conditions. The result: 5×5 debayering results in 40% out of match to the expected colors vs 13% for the JAI Apex 3-CMOS camera!

More advanced color imaging features

JAI’s Apex 3-CMOS machine vision cameras provide additional advanced features aside from excellent color fidelity and highlighted as follows:

Color Space conversion: Color data from the camera can be provided using built in conversions to several color spaces including sRGB, Adobe RGB, CIE XYZ and HSI. Custom RGB conversions can also be done using the cameras color matrix circuit.
Color Enhancer Function: Allows the 3-CMOS cameras to “boost” the intensity of 6 colors to help features stand out, such as the red color of blood vs surrounding tissue in a medical application. Additionally, degree’s of edge enhancement can be to increase the contrast of color boundaries.
Color Binning: While most Bayer cameras do not offer this, due to the prism architecture of the 3-CMOS cameras, you can easily bin pixels by 1×2, 2×1 and 2×2 to increase sensitivity, reduce shot noise and / or increase the frame rate.
Color temperature presets from 3200K, 5000K, 6500K and 7000K

All of these features, along with reduced costs for 3-CMOS color cameras, now make this a very attractive solution for demanding color applications! Applications in eye diagnostics, pathology, surgical imaging, meat/food inspection, print inspection and automotive color matching are a few that would highly benefit from the JAI Apex 3-CMOS camera series.

Need to proof 3-CMOS / 3-CCD prism based cameras will enhance your application? Let’s discuss sending you a demo camera!

Currently there are 6 new CMOS models outlined below and full specifications can be found HERE.

1st Vision is the leading provider of industrial imaging components with over 100 years of combined imaging experience. Do not hesitate to contact us regarding the new prices of the 3-CMOS cameras!

Be sure to visit our related blogs on 3-CCD and Prism based cameras

How does a 3CCD camera improve color accuracy and spatial resolution versus standard Bayer color cameras?

White Paper – Learn about High Dynamic Range (HDR) Imaging techniques for Machine Vision

White Paper -How does prism technology help to achieve superior color image quality?

March 22, 2018March 26, 2018

Which Industrial camera would you use in low light?

Our job as imaging specialists is to help our customers make the best decisions on which industrial camera and image sensor works best for their application. This is not a trivial task as there are many data points to consider, and in the end, a good image comparison test helps provide the true answer. In this blog post, we conduct another image sensor comparison for low light applications testing a long time favorite e2V EV76C661 Near Infra Red (NIR) sensor to the new Sony Starvis IMX178 and Sony Pregius IMX174 image sensor using IDS Imaging cameras.

An Industrial camera can be easily selected based on resolution and frame rates, but image sensor performance is more challenging. We can collect data points from the camera EMVA1288 test results and spectral response charts, but one can not conclude on what is best for the application based on one data point. In many cases, several data points need to be reviewed to start making an educated decision.

We started this review comparing 3 image sensors to determine which ones would perform best in low light applications.

Below is a chart comparing the e2v EV76C661 NIR, Sony Starvis IMX178 and , Sony Pregius IMX174 image sensors found in the IDS Imaging UI-3240NIR, UI-3880CP and UI-3060CP cameras using EMVA1288 data to start. This provides us with accurate image sensor data to evaluate.

image sensor comparison — Table 1: Sensor comparison data

Spectral response cufves — Camera Spectral Response curves

We also look at the Quantum Efficiency (QE) curves for the sensors to see the sensor performs over the light spectrum as seen to the left. (As a note, QE is the conversion of photon to an electrical charge (electrons)

For this comparison, our objective is to determine which sensor will perform best in low light applications with broadband light. From table 1, the IMX178 has very low absolute sensitivity (abs sensitivity) with taking ~ 1 photon to help make a adequate charge, however the pixels are small (2.4um), so maybe not gather light as well as larger pixels. It does have the best dark noise characteristics however. In comparison, the e2V sensor has 9.9 photons for abs sensitivity (not as good as 1 photon) and has a larger pixel size (bigger is better to collect light). The IMX174 proves to be interesting as well with the largest pixel of 5.86um and the highest QE @ 533nm.

Using the data from the spectral response curves however, helps give us more insight across the light spectrum. Given we are using a NIR enhanced camera, we will have significant more conversion of light to a create a charge on the sensor across most of the light spectrum. In turn, we expect we’d see brighter images from the e2V NIR IDS UI-3240 NIR camera.

As a note, one more data point is to look at the pixel well depth. Smaller pixels will saturate faster making the image brighter, so if other variables were close, this may also be taken into consideration.

As one can see, this is not trivial, but evaluating many of the data points, can give us some clues, but testing is really what it takes! So, lets now compare the images to see how they look.

The following images were taken with the same exposure, lens + f-stop in the identical low light environment. In the 2nd image, the e2v image sensor in the IDS-UI-3240CP NIR provides the brighter image as some of the data points started to indicate. The IDS UI-3060CP-M (IMX174) is second best.

In low light situations, we can always add camera gain, but we pay the price of adding noise to the image. Depending on the camera image sensor, some have the ability to provide more gain than others. This is another factor to review when considering adding gain. We need to also take into account read noise as this will get amplified with gain. Our next part of our test is to turn up the gain to see how we compare.

The following set of images was taken again with the same lens + f-stop, lighting, but with gain at max for each camera.

The IDS-UI-3060CP-M has the highest gain available, but still keeps the read noise relatively low with 6 electrons. This in low light WITH gain, gives us a nice image in nearly dark environments.

Conclusion
We can review the data points until we are blue in the face and they can be very confusing. We can however take in all the data and help make some more educated decisions on which cameras to test. For example in the first test, we had a good idea the NIR sensor would perform well looking a the QE curves along with other data. In our second test, we may have seen the UI-3060CP had 24X gain vs others still with low read noise, giving an indication, we’d have relatively clean image.

In the end, 1st Vision’s sales engineers will help provide the needed information and help conduct testing for you! We spend a lot of time in our lab in order to provide first hand information to our customers!

1st Vision is the leading provider of industrial imaging components with over 100 years of combined imaging experience. Do not hesitate to contact us to discuss your applications!

Just a few foot notes regarding this blog post:

Magnification of the images differs due to sensor size. Working distance of the cameras was kept identical in all setups and focused accordingly with distance.

This topic can be very complex! If we were to dig in even deeper, we’d take into consideration charge convergence of the pixel which effects sensitivity aside from looking at just QE!.. That’s probably another blog post!

As a reference, this image was taken with an Iphone and set to best represent what my eye viewed during our lab test. Note that the left container with markers was non-distinguishable to the human eye

Clipart courtesy of clipartextra.com