The JAI WAL-1001-GE and -2001- are compact GigE 1K SWIR line scan cameras with InGaAs sensors designed for high-speed industrial inspection using a high-sensitivity InGaAs sensor. While there are a number of area scan SWIR cameras on the market, line scan SWIR is a smaller niche. But if it gives you a competitive edge or innovative solution – it’s not a niche for you.
JAI WAL-1001-GE SWIR line scan camera – Courtesy JAI
SWIR sees things that VIS cannot – Courtesy JAI
Optional review on SWIR and line scan
Just in case you’re coming at this from a VIS (visible spectrum) and/or area scan context…
SWIR – Short Wave Infra Red – uses a segment of the spectrum not visible to the human eye nor CMOS sensors used for VIS imaging. But SWIR is very effective at “seeing” things not revealed in VIS. For more on SWIR see our blog and/or knowledge-based article.
Line scan – unlike area scan images that capture a large 2D view and whose framerates are limited by data volumes, line scan sensors are just one or two pixels wide while hundreds or thousands of pixels long.
Two example applications before camera details
Here are two representative SWIR line scan applications. There are many others as well.
Semiconductor inspection: Detect flawed wafers early in production to avoid shipping flawed product, to reduce production costs, and and increase yield.
VIS image (left) only finds the large crack; SWIR image (right) also finds smaller upper crack – Courtesy JAI
Plastic seal inspection: SWIR imaging reveals contrasts that are not visible with standard visible-light imaging. In this example, the heat seals in a plastic bag needed to be inspected to ensure that the seal was strong and consistent. The bags are produced in a continuous production process, where a single line-scan camera can capture the seams as the product moves through the system.
SWIR clearly reveals seal quality better than VIS – Courtesy JAI
JAI WAVE WAL 1001 GE and -2001- camera highlights
For full details, including data sheets, tabular overview, etc., see both the SWIR line scan and area scan JAI WAVE cameras at our website. Here we call out just a few highlights.
1024 px at 29 kHz or 2048 px at 40 kHz:
(WAL-1001-GE and WAL-2001-GE, respectively)
1k at 29 kHz or 2k at 40 kHz – Courtesy JAI
Sensor layouts on 1001 vs 2001 models:
Single row of pixels on 1001, vs. 2 stagger-offset rows on 2001 – Courtesy JAI
How much resolution do you need?
Resolution outcomes from 1001 vs 2001 models – Courtesy JAI
Key point: The 2k camera captures with both of the offset lines, this offset will reveal sub pixel details revealing smaller defects.
It will also oversample the sensor running at twice the normal speed to get the same level of detail in the movement direction. It will then output an image with the equivalent of a 2k sensor with half the pixel size.
Doubling down on the 2 row camera, for emphasis
While the 1k camera is already enough for many applications, let’s spend a moment longer on the 2 row WAL-2001-GE model. The biggest value proposition in this model is:
Doubled resolution for enhanced defect detection A 0.5-pixel offset design effectively doubles sampling density, enabling reliable detection of sub-pixel-scale defects beyond the limits of conventional 1K cameras.
But it’s also worth noting:
Optimized cost-to-performance ratio
The dual-row 1K sensor configuration replaces a native 2K sensor, delivering high-resolution infrared imaging while reducing overall system cost.
…and
Internal image synthesis for simplified system design The 2K image is synthesized in real time inside the camera, eliminating the need for an external acquisition card and reducing both system complexity and latency.
Resolution differences
Below, created under identical conditions, see the expected higher resolution with the 2k camera utilizing the 2 rows of pixels offset against each other.
Comparing resolution outcomes on an intentionally challenging example – Courtesy JAI
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The Wave WAA-1300-GE-TEC combines visible and short-wave infrared (SWIR) sensitivity in a single camera, enabling enhanced material contrast, improved defect detection, and more reliable inspection results. With sensitivity from 400 nm to 1700 nm, the camera can reveal features and material characteristics that may not be visible using standard imaging technologies.
Wave WAA-1300-GE-TEC SWIR camera – Courtesy JAI
Applications
Semiconductor alignment:
SWIR sees through silicon layers to find alignment marks. This enables precision through successive process layers. Image courtesy of JAI.
Fruit and vegetable sorting:
VIS + SWIR working together can identify bruising, ripeness levels, early spoilage, and more. Image courtesy of JAI.
Laser beam profiling:
SWIR enables measuring beam shape, intensity distribution, and alignment. Image courtesy of JAI.
Recycling and material sorting:
In VIS two clear plastic bottles might appear the same, but SWIR can see their different response in it’s portion of the spectrum – allowing different handling. SWIR enables measuring beam shape, intensity distribution, and alignment. Image courtesy of JAI.
Some of the key Wave WAA-1300-GE-TEC VIS SWIR features – Courtesy JAI
Utilize diverse spectral responses to your advantage
The application areas above are just representative, and are not meant to be exhaustive. The key point is that diverse materials provide differing spectral responses under appropriate light (including natural light).
Applications may be designed to identify and differentiate materials according to their spectral properties. Sensors, cameras, lighting, and lenses are available for machine vision applications that draw upon each of UV, VIS, IR, NIR, SWIR, MWIR, and LWIR portions of the spectrum. And combinations thereof – like the VisSWIR JAI Wave WAA-1300-GE-TEC.
About you: We want to hear from you! We’ve built our brand on our know-how and like to educate the marketplace on imaging technology topics… What would you like to hear about?… Drop a line to info@1stvision.com with what topics you’d like to know more about.
Short Wave Infrared (SWIR) imaging is enjoying double-digit growth rates, thanks to improving technologies and performance, and innovative applications. Unlike visible-light sensors, SWIR cameras can image through silicon, plastics, and other semitransparent materials. That’s really effective for many quality control applications, materials sorting and inspection, crop management, fruit sorting, medical applications, and more.
Visible vs. SWIR image pairs – Courtesy Allied Vision – a TKH Vision brand
Unlike CMOS sensors, from which high-quality images are reliably derived under wide operating conditions, SWIR sensors typically need “tuning” relative to temperature and exposure duration. First generation SWIR cameras sometimes generated images that while useful, were a bit rough and with certain limitations in the extreme. SWIR camera manufacturers have been innovating solutions to raise the performance of their cameras.
What’s the problem?
In short-wave infrared (SWIR) imaging applications, camera operation points such as exposure time, gain and bit-depth need to be adapted depending on the inspection task at hand. Image sensor defects such as defective pixels and image non-uniformities – inherent to SWIR sensors – are sensitive to the aforementioned operations points.
Unless controlled, image quality can suffer
Consider the following image:
The gray field is intentionally unexciting as a flat field baseline without a target. The white dots are undesired defect pixels, an unfortunate characteristic that one can thankfully correct through interpolation. This image is meant to show “what we do NOT want”.
The four parameters exposure setting, temperature, bit-depth, and gain may collectively be called the “Operating Point” of a SWIR sensor, as together they have a significant bearing on image quality. Through manual or automated adjustments, one can optimize image outcomes.
Harnessing variable parameters into manageable corrections – Courtesy Allied Vision – a TKH Vision brand
In this blog, we provide context for these concepts. And we introduce Dynamic Operating Point Optimization (DOPO) as an automated innovation available in the fx series of SWIR cameras offered by SVS Vistek / Allied Vision.
fx series SWIR cameras – Courtesy SVS Vistek / Allied Vision – a TKH Vision brand
Before Dynamic Operating Point Optimization (DOPO)
SWIR cameras with some image correction capabilities – prior to DOPO we’ll describe in the next section – certainly improved image quality. Largely via defect pixel correction (DPC) and non-uniformity correction (NUC).
Defect pixel correction (DPC) is achieved by replacing the “hot” or “dead” pixel value by the average value of its nearest neighbors. As long as there isn’t a cluster defect with multiple adjacent defect pixels (typically identified and rejected at manufacturing quality control), this is an effective solution.
Non-uniformity correction (NUC) is a bit more complex, but worth understanding. The non-uniformities arise in thermal imaging due to variations in sensitivity among pixels. If uncorrected, the target image could be negatively impacted with striations, ghost images, flecks, etc.
Factory configuration of each camera, before finalizing testing and shipping, adapts for the nuanced differences among individual sensors. Correction tables are created and stored onboard the camera, so that the user receives a camera that already compensates for the variations.
In reality it’s a bit more complicated
In fact defect pixels aren’t always simply hot or dead: they may appear only at certain operating points (exposure duration, temperature, gain, bit-depth, or combinations thereof).
Likewise for non-uniformity characteristics.
So that factory configuration mentioned above, while satisfactory for many applications, is a one size fits all best hope compromise, relative to the tools (then) available to the camera manufacturer and the price point the market would accept. Just as with t-shirts and socks, one size doesn’t really fit every need.
Dynamic Operating Point Optimization (DOPO)
Allied Vision has introduced dynamic operating point optimization (DOPO) to further automate SWIR cameras’ capacity to adapt to changes brought about by exposure time, temperature, gain, and bit depth. Let’s examine the graphic below to understand DOPO and the added value it delivers.
First consider the Y-axis, “Image Quality”. Looking at the flat-field gray block, clearly one would prefer the artifact-free characteristics of the upper region.
Also note the X-axis, “Sensor Temperature / Exposure Time”, for an uncooled thermal sensor. (Note that some thermal cameras do have sensor cooling options, but that’s a topic for another blog.) See the black line “No correction” sloping from upper left to lower right, and how the number of image artifacts grows markedly with exposure time. Without correction the defect pixels and sensor non-uniformities are very apparent.
Flat-field image quality with and without corrections – Courtesy Allied Vision – a TKH Vision brand
Now look at the gray lines labeled “NUC+DPC”. For a factory calibrated camera optimized for a sensor at 30 degrees Celsius and a 25ms exposure, the NUC and DPC corrections indeed optimize the image effectively – right at that particular operating point. And it’s “not bad” for exposure times of 20ms or 15ms to the left, or 30ms or 35ms to the right. But the corrections are less effective the further one gets away from that calibration point.
Finally let’s look at the zig-zag red lines labeled “DOPO”. Instead of the “one size best-guess” factory calibration, represented by the grey lines, a DOPO equipped camera is factory calibrated at up to 600 correction maps, varying each of exposure time, temperature, gain and bit depth across a range of steps, and building maps that represent all the stepwise permutations.
Takeaway: DOPO provides a set of correction tables not just one
So with DOPO providing a set of correction tables, the camera can automatically apply the best-fit correction for whatever operating point is in use. That’s the key point of DOPO. Unlike single-fit correction tables, with so many calibrated corrections under DOPO, the best-fit isn’t far off.
Give us some brief idea of your application and we will contact you to discuss camera options.
Thermal imaging with SWIR cameras – plenty of choices
There are a number of options as one selects a SWIR camera. Is your choice driven mostly by performance under extreme conditions? Size? Cost? A combination of these?
Call us at 978-474-0044. We can guide you to a best-fit solution, according to your requirements.
The key message of this blog is to introduce Dynamic Operating Point Optimization – DOPO – as a set of factory calibration tables and the camera’s ability to switch amongst them. An equally important takeaway is that you may or may not need DOPO for a particular thermal imaging application. There are many SWIR options, in cameras and lenses, and we can help you choose.
About you: We want to hear from you! We’ve built our brand on our know-how and like to educate the marketplace on imaging technology topics… What would you like to hear about?… Drop a line to info@1stvision.com with what topics you’d like to know more about.
While we humans can only see what we’ve named to be visible light, bees can see UV light! Some camera sensors register IR wavelengths! Some cameras can sense both visible light and on through NIR and SWIR.
In this piece we focus on applications that benefit from combined VIS-SWIR solutions, from 400 nm through 2.5 nm.
Deconstructing the electromagnetic spectrum into it’s commonly known constituent regions
Example applications
Just to whet the appetite, consider the 4 sets of image pairs below. In each case, the leftmost image was captured with visible wavelengths, while the righthand image utilized SWIR portions of the spectrum. These pairs were chosen to highlight the compelling power of SWIR to identify features that are not apparent in the visible portion of the spectrum.
VIS-SWIR image pairs – Courtesy Allied Vision – a TKH company
For certain applications, one wouldn’t need the human-visible images, of course, as with machine vision the whole point is to automate the image processing and corresponding actions. So for counterfeit banknote detection, bottle fill level monitoring, materials identification, or crop monitoring, one might just design for the SWIR portion of the spectrum and ignore the VIS.
Vein imaging application overlays SWIR image of veins into visible image of patient forearm –Image courtesy TAMRON
But some applications might benefit from both the VIS and the SWIR images. For example, the vein imaging application might require a VIS reference image as well as a SWIR-specific image, for patient education and/or medical records.
Monitor moisture levels in crops from airborne drone – Image courtesy TAMRON
For the crop monitoring application above, the VIS spectrum clearly orients trees, hills, buildings, and roadways. Meanwhile pseudo-color-mapping shows the varied moisture levels as sensed in the SWIR portion of the spectrum.
The range of potential applications combining VIS and SWIR is staggering. One can improved on one’s own or a competitor’s previous application. Or innovate something altogether new.
Sensors that register both VIS and SWIR wavelengths
Sony’s IMX992 and IMX993 sensors utilize Sony’s SenSWIR technology, such that a single sensor and camera may be deployed across the combined VIS and SWIR portions of the spectrum. Without such sensors, a VIS SWIR solution would require at least two separate cameras – one each for VIS and SWIR, respectively. That would add unnecessary expense, takes up more space, and require camera and image synchronization.
Now there are cameras, such as several in Allied Vision’s Alvium series, in which Sony’s SenSWIR sensors are embedded. With several interface options, including mipi, USB3 Vision, and 5GigE Vision:
Mipi, USB3 Vision, and 5GigE Vision interface options – Courtesy Allied Vision – a TKH Company
Lens manufacturers doing their part
One of the beauties of the free-market system, together with agreements on standards for interfaces and lens mounts, is that each innovator and manufacturer can focus on what he does best. Sensor manufacturers bring out new sensors. Camera designers embed those sensors and provide programming controls, communications interfaces, and lens mounts. And optics professionals design and produce lenses. The benefits from a range of choices, performance options, and price points.
Navitar VIS-SWIR lenses
Navitar’s ZOOM 7000-2 macro lens imaging system delivers superb optical performance and image quality for visible and SWIR imaging. Their robust design ensures reliability even in harsh environments. ZOOM 7000-2 macro lenses are ideal for applications, such as machine vision, scientific and medical imaging applications.
ZOOM 7000-2 VIS-SWIR lens – Courtesy Navitar
In fact there are three models in the series:
Each model has its application – but only the middle one is designed explicitly for VIS-SWIR – Courtesy Navitar
Kowa FC24M multispectral lenses
Kowa’s FC24M C-mount lens series are manufactured with wide-band multi-coating. That minimizes flare and ghosting from VIS through NIR. These lenses are also compelling for a number of other reasons, including wide working range (as close as 15 cm MOD), durable construction, and a unique close distance aberration compensation mechanism.
FC24M C-mount lens series – Courtesy Kowa
That “floating feature” creates stable optical performance at various working distances. Internal lens groups move independently of each other, which optimizes alignment compared to traditional lens design.
Tamron Wide-band SWIR lenses
Other lensing options include Tamron’s Wide-band SWIR lenses. While the name says SWIR, in fact they are VIS-SWIR. Designed for compatibility with Sony’s IMX990 and IMX991 SenSWIR sensors, you have even more lens choices. Call us at 978-474-0044 if you’d like us to help you navigate to best-fit components in cameras, lensing, and lighting, for your particular application.
About you: We want to hear from you! We’ve built our brand on our know-how and like to educate the marketplace on imaging technology topics… What would you like to hear about?… Drop a line to info@1stvision.com with what topics you’d like to know more about.
