Recently released Goldeye G/CL-008 XSWIR cameras with QVGA resolution extended range InGaAs sensors offer two sensitivity options: up to 1.9 µm or 2.2µm.
From SWIR into Extended SWIR. Image courtesy of Allied Vision Technologies.
The Extended Range (ER) InGaAs sensor technology integrated into the new Goldeye XSWIR models provides high imaging performance beyond 1.7 µm.
The cut-off wavelength can be shifted to higher values by increasing the amount of Indium vs. Gallium in an InGaAs compound. Corresponding sensors can only detect light below the cut-off wavelength. In the Goldeye XSWIR cameras there are four different sensors with VGA and QVGA resolution and cut-off wavelength at 1.9 µm or 2.2 µm that provide very high peak quantum efficiencies of > 75%.
Indium : Gallium ratio determines cut-off wavelength; image courtesy of Allied Vision
The new Goldeye XSWIR models are:
Table showing 4 sensor options for Goldeye 008 XSWIR; courtesy of Allied Vision
In these cameras the sensors are equipped with a dual-stage thermo-electric cooler (TEC2) to cool down the sensor temperature by 60K vs. the housing temperature. Also included are image correction capabilities like Non-Uniformity Correction (NUC) and 5×5 Defect Pixel Correction (DPC) to capture high-quality SWIR images beyond 1.7 µm.
Goldeye XSWIR cameras are available with two sensor options. The 1.9µm version detects light between 1,100nm to 1,900nm and the 2.2 µm version from 1,200 – 2,200nm.
Response curves for two respective sensors; images courtesy of Allied Vision
Industrial grade solution for an attractive price: Other sensor technologies available to detect light beyond 1,700 nm based on materials like HgCdTe (MCT), Type-II Superlattice (T2SL), or Colloidal Quantum Dots (CQD) tend to be very expensive. The Goldeye XWIR Extended Range (ER) InGaAs sensors have several advantages including cost-effective sensor cooling via TEC, high quantum efficiencies, and high pixel operability (> 98.5%).
MCT or T2SL sensor-based SWIR cameras typically require a very strong sensor cooling using Stirling coolers or TEC3+ elements. By comparison the Goldeye XSWIR cameras are available for a comparatively low price.
The easy integrability and operation of ER InGaAs sensors makes them attractive for industrial applications, including but not limited to:
Laser beam analysis
Spectral imaging in industries like recycling, mining, food & beverages, or agriculture
Medical imaging: e.g. tissue imaging due to deeper penetration of longer wavelengths
So you want to do an in-line measurement, inspection, identification and/or guidance application in automotive, electronics, semiconductor or factory automation. Whether a new application or time for an upgrade, you know that Teledyne DALSA’s Z-Trak 3D Laser Profiler balances high performance while also offering a low total cost of ownership.
In this 2nd Edition release we update the Z-Trak family overview with the addition of the new LP2C 4k series, bringing even more options along the price : performance spectrum. From low cost and good enough, through more resolution as well as fast, and all the way to highest resolution, there are a range of Z-Trak profiles to choose from.
Z-Trak 3D Laser Profiler
The first generation Z-Trak product, the LP1, is the cornerstone of the expanded Z-Trak family, now augmented with the Z-Trak2 group (V-series and the S-series), plus the LP2C 4k series. Each product brings specific value propositions – here we aim to help you navigate among the options.
Respecting the reader’s time, key distinctions among the series are:
LP1 is the most economical 3D profiler on the market – contact us for pricing.
Z-Trak2 is one of the fastest 3D profilers on the market – with speeds to 45kHz.
LP2C 4k provides 4,096 profiles per second at resolution down to 3.5 microns.
To guide you effectively to the product best-suited for your application, we’ve prepared the following table, and encourage you to fill in the blanks, either on a printout of the page or via copy-past into a spreadsheet (for your own planning or to share with us as co-planners).
3D application key attributes
Compare your application’s key attributes from above with some of the feature capacities of the three Z-Trak product families below, as a first-pass at determining fit:
Unless the fit is obvious – and often it is not – we invite you to send us your application requirements. We we love mapping customer requirements, so please send us your application details in our form on this contact link; or you can send us an email to info@1stvision.com with the feedback from your 3D application’s “Key questions” above.
In addition to the parameter-based approach to choosing the ideal Z-Trak model, we also offer an empirical approach – send in your samples. We have a lab set up to inspect customer samples with two or more candidate configurations. System outputs can then be examined for efficacy relative to your performance requirements, to determine how much is enough – without over-engineering.
We recently published a TechBrief “What is MTF?” to our Knowledge Base. It provides an overview of the Modulation Transfer Function, also called the Optical Transfer Function, and why MTF provides an important measure of lens performance. That’s particularly useful when comparing lenses from different manufacturers – or even lenses from different product families by the same manufacturer. With that TechBrief as the appetizer course, let’s dig in a little deeper and look at how to read an MTF lens curve. They can look a little intimidating at first glance, but we’ll walk you through it and take the mystery out of it.
Figure A. Both images created with lenses nominally for similar pixel sizes and resolution – which would you rather have in your application?
Test charts cluster alternating black and white strips, or “line pairs”, from coarse to fine gradations, varying “spatial frequency”, measured in lines / mm, in object space. The lens, besides mapping object space onto the much smaller sensor space, must get the geometry right in terms of correlating each x,y point to the corresponding position on the sensor, to the best of the lens’ resolving capacity. Furthermore, one wants at least two pixels, preferably 3 or more, to span any “contrast edge” of a feature that must be identified.
So one has to know the field of view (FOV), the sensor size, the pixel pitch, the feature characteristics, and the imaging goals, to determine optical requirements. For a comprehensive example please see our article “Imaging Basics: How to Calculate Resolution for Machine Vision“.
Figure B. Top to bottom: Test pattern, lens, image from camera sensor, brightness distribution, MTF curve
Unpacking Modulation Transfer Function, let’s recall that “transfer” is about getting photons presented at the front of the lens, coming from some real world object, through glass lens elements and focused onto a sensor consisting of a pixel array inside a camera. In addition to that nifty optical wizardry, we often ask lens designers and manufacturers to provide lens adjustments for aperture and variable distance focus, and to make the product light weight and affordable while keeping performance high. “Any other wishes?” one can practically hear the lens designer asking sarcastically before embarking on product design.
So as with any complex system, when transferring from one medium to another, there’s going to be some inherent lossiness. The lens designer’s goal, while working within the constraints and goals mentioned above, is to achieve the best possible performance across the range of optical and mechanical parameters the user may ask of the lens in the field.
Consider Figure B1 below, taken from comprehensive Figure B. This shows the image generated from the camera sensor, in effect the optical transfer of the real world scene through the lens and projected onto the pixel array of the sensor. The widely-spaced black stripes – and the equally-spaced white gaps – look really crisp with seeming perfect contrast, as desired.
Figure B1: Image of progressively more line pairs per millimeter (lp/mm)
But for the more narrowly-spaced patterns, light from the white zones bleeds into the black zones and substantially lowers the image contrast. Most real world objects, if imaged in black and white, would have shades of gray. But a test chart, at any point position, is either fully black or fully white. So any pixel value recorded that isn’t full black or full white represents some degradation in contrast introduced by the lens.
The MTF graph is a visual representation of the lens’ ability to maintain contrast across a large collection of sampled line pairs of varying widths.
Let’s look at Figure B2, an example MTF curve:
Figure B2: Example of MTF graph
the horizontal axis denotes spatial frequency in line pairs per millimeter; so near the origin on the left, the line pairs are widely spaced, and progressively become more narrowly spaced to the right
the vertical axis denotes the modulation transfer function (MTF), with high values correlating to high contrast (full black or full white at any point), and low values representing undesirable gray values that deviate from full black or full white
The graph in Figure B2 only shows lens-center MTF, for basic discussions, and does not show performance on edges, nor take in account f# and distance. MTF, and optics more generally, are among the more challenging aspects of machine vision, and this blog is just a primer on the topic.
Give us some brief idea of your application or your questions – we will contact you to assist
In very general terms, we’d like a lens’ MTF plot to be fairly close to the Diffraction Limit – the theoretical best-case achievable in terms of the physics of diffraction. But lens design being the multivariate optimization challenge that it is, achieving near perfection in performance may mean lots of glass elements, taking up space, adding weight, cost, and engineering complexity. So a real-world lens is typically a compromise on one or more variables, while still aiming to achieve performance that delivers good results.
Visualizing correlation between MTF plot and resultant image – MORITEX North America
How good is good enough? When comparing two lenses, likely in different price tiers that reflect the engineering and manufacturing complexity in the respective products, should one necessarily choose the higher performing lens? Often, yes, if the application is challenging and one needs the best possible sensor, lighting and lensing to achieve success.
But sometimes good enough is good enough. It depends. For example, do you “just” need to detect the presence of a hole, or do you need to accurately measure the size of the hole? The system requirements for the two options are very different, and may impact choice of sensor, camera, lens, lighting, and software – but almost certainly sensor and lensing. Any lens can find the hole, but a lens capable of high contrast is needed for accurate measurement.
Here’s one general rule of thumb: the smaller the pixel size, the better the optics need to be to obtain equivalent resolution. As sensor technology evolves, manufacturers are able to achieve higher pixel density in the same area. Just a few years ago the leap from a VGA sensor to 1 or 5 MegaPixels (MP) was considered remarkable. Now we have 20 and 50 MP sensors. That provides fantastic options to systems-builders, creating single-camera solutions where multiple cameras might have been needed previously. But it means one can’t be careless with the optical planning – in order to achieve optimal outcomes.
Not all lens manufacturers express their MTF charts identically, and testing methods vary somewhat. Also, note that many provide two or even three lens families for each category of lenses, in order to provide customers with performance and pricing tiers that scale to different solutions requirements. To see an MTF chart for a specific lens, click first on a lens manufacturer pages such as Moritex, then on a lens family page, then on a specific lens. Then find the datasheet link, and scroll within the datasheet PDF to find the MTF curves and other performance details.
Besides the theoretical approach to reading specifications prior to ordering a lens, sometimes it can be arranged to send samples to our lab for us to take sample images for you. Or it may be possible to test-drive a demo lens at your facility under your conditions. In any case, let us help you with your component selection – it’s what we do.
Finally, remember that some universities offer entire degree programs or specializations in optics, and that an advanced treatment of MTF graph interpretation could easily fill a day-long workshop or more – assuming attendees met certain prerequisites. So this short blog doesn’t claim to provide the advanced course. But hopefully it boosts the reader’s confidence to look at MTF plots and usefully interpret lens performance characteristics.
Acknowledgement / Credits: Special thanks to MORITEX North America for permission to include selected graphics in this blog. We’re proud to represent their range of lenses in our product offerings.
Effective machine vision outcomes depend upon getting a good image. A well-chosen sensor and camera are a good start. So is a suitable lens. Just as important is lighting, since one needs photons coming from the object being imaged to pass through the lens and generate charges in the sensor, in order to create the digital image one can then process in software. Elsewhere we cover the full range of components to consider, but here we’ll focus on lighting.
While some applications are sufficiently well-lit without augmentation, many machine vision solutions are only achieved by using lighting matched to the sensor, lens, and object being imaged. This may be white light – which comes in various “temperatures”; but may also be red, blue, ultra-violet (UV), infra-red (IR), or hyper-spectral, for example.
LED bar lights are a particularly common choice, able to provide bright field or dark field illumination, according to how they are deployed. The illustrations below show several different scenarios.
Example uses of LED bar lights
LED light bars conventionally had to be factory assembled for specific customer requirements, and could not be re-configured in the field. The EFFI-Flex LED bar breaks free from many of those constraints. Available in various lengths, many features can be field-adapted by the user, including, for example:
Color of light emitted
Emitting angle
Optional polarizer
Built-in controller – continuous vs. strobed option
While the EFFI-Flex offers maximum configurability, sister products like the EFFI-Flex-CPT and EFFI-Flex-IP69K offer IP67 and IP69 protection, respectively, ideal for environments requiring more ruggedized or washdown components.
SWIR LED bar, backlight, and ringlight
Do you have an application you need tested with lights? Contact us and we can get your parts in the lab, test them and send images back. If your materials can’t be shipped because they are spoilable foodstuffs, hazmat items, or such, contact us anyway and we’ll figure out how to source the items or bring lights to your facility.
Test and optimize lighting with customer materials
