Imatest

Embedded Vision Summit 2026
2026-05-11 08:00 - 2026-05-13 17:00 (America/Denver) | Santa Clara, California, Santa Clara, CA, United States
Imatest will be at Booth #907 of the Premier Conference for Innovators Incorporating Computer Vision and Physical AI in Products.
Key Topics Include

View All Sessions

Physical AI

Keynote: Scaling Down Is the New Scaling Up
From Generative AI to Physical AI: Enabling VLM/VLA Multimodal Performance on Enhanced NPX6 NPU IP
No RISC, No Reward:
Unlocking Extreme Efficiency in Physical AI with RISC-V

Real-World Autonomy

Pushing the Limits: Sensing and Compute Requirements for Humanoid Robots
Building Trustworthy Autonomous Driving Systems: Waymo’s Holistic AI Safety Approach
Porting and Optimizing Advanced Vision-Language-Action Models for Embedded Autonomous Systems

Prototype to Product

Vision AI in Retail: From Lab to 2,000+ Autonomous Checkout Points of Sale
What Kills Industrial Vision AI Pilots? (Hint: It’s Not Model Performance)
From Prototype to Production: What Vision Teams Wish They Knew at 100 Devices

Emerging Edge AI

Small but Mighty: The Rise of Small Language Models and the Future of AI
Beyond “What’s in the Image?”: World Models for Understanding and Predicting
Efficient State-Space Models

Colorado Photonics Rocky Mountain Summit & Expo 2026
2026-04-17 | Denver Marriott Westminster, 7000 Church Ranch Blvd, Westminster, CO, 80021, United States
Imatest is exhibiting at the CPIA Rocky Mountain Summit & Expo booth 6.
This is an unparalleled opportunity to connect with industry leaders and innovators. The Rocky Mountain Summit & Expo offers a unique opportunity to learn about new developments, connect with professionals, and showcase your expertise in photonics and optics.

Expand Your Expertise: Discover the latest advancements in photonics and gain insights from world-class speakers and industry experts.
Forge New Connections: Meet and network with professionals, researchers, and organizations that are shaping the photonics industry in the Rocky Mountain region and beyond.
Seize Opportunities: Whether you attend, sponsor, or exhibit, this event is a platform to grow your professional contacts, explore collaborations, and unlock new business opportunities.
Showcase Innovation: Learn from the pioneers in photonics and explore cutting-edge solutions that are transforming industries.

EI2026 Short Course: Camera Simulation for Predicting Information Metrics and Machine Vision Performance
2026-03-01 14:00 - 17:00 (America/Los_Angeles) | Hyatt Regency San Francisco Airport, 1333 Bayshore Highway, Burlingame, CA, 94010, United States
Instructor: Norman L. Koren
When: Sunday, March 1st 2:00 PM – 5:00 PM PST
Benefits:

Understand the fundamentals of information capacity and how it relates to conventional SFR and noise measurements,
Understand the information metrics (information capacity and others derived from information theory), and learn how they relate to system performance,
Learn the fundamentals of camera system simulation, including preparing the image (typically a test chart), determining the lens degradations, image sensor noise model, and Image Signal Processing (ISP),
Learn how to determine the effects of each system component or image processing step on the system performance.

Course description:
This course introduces the basics of information theory, shows why the key information metrics (information capacity and SNRi) are superior to traditional metrics such as sharpness (SFR) and noise for characterizing camera performance, then show how to calculate them from test chart images.
Next, the course describes the camera performance simulator, including

Creating input images (usually test targets),
Simulating lens degradations,
Modeling the image sensor noise and ISP (Image Signal Processing),
Displaying results, including the standard performance metrics and new information metrics.

This course will discuss C4, the information capacity measured directly from ISO 12233-compliant 4:1 contrast slanted edges, and show how it can characterize performance over a range of illumination. Finally, it includes a discussion work to correlate information metrics with machine vision performance.

Intended Audience: Engineers who are tasked with designing camera systems for a variety of applications, often in the automotive and medical industries. They typically have degrees in sciences such as physics or in electrical or mechanical engineering, but may be new to image science. Ideally, they should have some experience in imaging system design, though the course will accommodate beginners with limited engineering experience.

Norman Koren became interested in photography while growing up near the George Eastman Museum in Rochester, NY. He received his BA in physics from Brown University (1965) and his masters in physics from Wayne State University (1969), then worked in the computer storage industry simulating digital magnetic recording systems and channels for disk and tape drives from 1967-2001. He founded Imatest LLC in 2003 to develop software and test charts to measure the quality of digital imaging systems.
EI2026 Details Registration

Electronic Imaging 2026 (EI2026)
2026-03-01 - 2026-03-05 | Hyatt Regency San Francisco Airport, 1333 Bayshore Highway, Burlingame, CA, 94010, United States
Imatest Presented:

March 1: Short Course: Information Metrics for Machine Vision
March 3 11:00: Paper: Toward Fair and Accurate Camera Testing: Validation of Skin Tone Test Charts with Real Human Data
March 3, 3:30: Paper: Image Sensor Noise model for Image System Simulation
March 3, 3:30: Panel session: road markings and signage for autonomous vehicles.
March 4, 9:30: Paper: Centroid to Low-Pass Edge Fitting in ISO 12233 eSFR: Accuracy and Impact on Digital Imaging Information Metrics
March 4, 3:30: Paper: Information-based Dynamic Range
March 4, 4:30: Paper: A method for calculating NIR bandpass-adjusted Optical Densities for better matching common standard test chart specifications.

Short Course: Camera Simulation for Predicting Information Metrics and Machine Vision Performance
Instructor: Norman L. Koren
When: Sunday, March 1st 2:00 PM – 5:00 PM PST
Benefits:

Understand the fundamentals of information capacity and how it relates to conventional SFR and noise measurements,
understand the information metrics (information capacity and others derived from information theory), and have a feeling of how it relates to system performance
learn about the latest work being done to correlate the information metrics with system performance
Learn the fundamentals of system simulation, including preparing the image (typically a test chart), determining the lens degradations and image sensor noise model
Know how to determine the effects of each system component or image processing step on the system performance.

Show More
Course description:
This course introduces the basics of information theory, shows why the key information metrics (information capacity and SNRi) are superior to traditional metrics such as sharpness (SFR) and noise for characterizing camera performance, then show how to calculate them from test chart images.
Next, the course describes the camera performance simulator, including

creating input images (usually test targets),
Simulating lens degradations,
Rhe image sensor noise model,
ISP (Image Signal Processing),
Results, including the standard and new information metrics.

This course will discuss C4, the information capacity measured directly from ISO 12233-compliant 4:1 contrast slanted edges, and show how it characterizes performance over a range of illumination. Finally, it includes a discussion work to correlate information metrics with machine vision performance.

Intended Audience: Engineers who are tasked with designing camera systems for a variety of applications, often in the automotive and medical industries. They typically have degrees in sciences such as physics or in electrical or mechanical engineering, but may not be well-versed in image science. Ideally, they should have some experience in imaging system design, though the course will accommodate beginners with limited engineering experience.
Norman Koren became interested in photography while growing up near the George Eastman House photographic museum in Rochester, NY. He received his BA in physics from Brown University (1965) and his masters in physics from Wayne State University (1969), then worked in the computer storage industry simulating digital magnetic recording systems and channels for disk and tape drives from 1967-2001. He founded Imatest LLC in 2003 to develop software and test charts to measure the quality of digital imaging systems.

Screenshot
“Toward Fair and Accurate Camera Testing: Validation of Skin Tone Test Charts with Real Human Data”
Megan Borek, Amelia Limbocker, Ellis Monk
Session: IQSP Skin Tone Capture and Image Quality I
Date: March 3rd
Time: 11:00 AM
Duration: 20 minutes
Accurate reproduction of diverse skin tones remains a persistent challenge for consumer cameras, with shortcomings in automatic exposure and white balance often leading to biased results. To address this, we are developing skin tone test charts designed to better represent real human skin across the full range of the Monk Skin Tone Scale. This work validates these charts using real human data collected through multiple methods. First, survey responses capture user perspectives on how their skin tones are represented in smartphone images and what they expect from their devices. Second, controlled photographic sessions with participants across the scale provide image data under varied lighting conditions and multiple exposure strategies, including gray card, spot metering, and bracketing, alongside participant-selected preferred
measurements from skin regions supplement the imaging data with objective ground truth. Together, these datasets allow us to evaluate and tune test chart behavior so that color and exposure responses align more closely with real skin. This validation represents a step toward fairer, more accurate camera testing standards, with implication for consumer photography as well as applications in medical, automotive, and security images.

“Image Sensor Noise model for Image System Simulation”
Norman L. Koren
Session: IQSP
Date: March 3rd
Time: 3:30 PM
Duration: 20 minutes
We present an image sensor noise model, which is part of a complete image system simulation that includes image generation, lens degradations, and ISP (Image Signal Processing), and can produce classic measurements (SFR, noise, etc.) as well as the new information metrics (information capacity, SNRi, etc.).
The noise model is derived from a classic Photon Transfer Curve (PTC) obtained from one or at most two raw (undemosaiced) images of a high dynamic range grayscale test chart. Image sensor noise is composed of three factors.
Show More

Dark noise, which includes electronic noise, dark current noise, and DSNU fixed-pattern noise. It is independent of amplitude.
Photon shot noise, which varies with the square root of the amplitude, and
PRNU fixed-pattern noise, which varies linearly with amplitude.

The coefficients for the three factors are determined using a Levenberg Marquardt optimization that provides an extremely close fit between the data to the measured PTC. The coefficients can also be derived from EMVA 1288 measurements, which are more detailed, but require a large number of
images to acquire.
We show how the model can predict performance over a wide range of conditions, most importantly, for low light.

Panel session: road markings and signage for autonomous vehicles.
Paul Romanczyk PhD
Session: AVM
Date: March 3rd
Time: 3:30 PM
Discussion relating to colors and spectral properties of various road elements, such as pavement markings and traffic signs, and how their properties influence the detectability by machine vision systems.

“From Centroid to Low-Pass Edge Fitting in ISO 12233 eSFR: Accuracy and Impact on Digital Imaging Information Metrics”
Sarah Kerr
Session: IQSP
Date: March 4
Time: 9:30 AM
Duration: 20 minutes
Edge localization estimation methods play a critical role in ISO 12233 eSFR analysis, influencing both sharpness results and downstream information capacity metrics. This paper evaluates the accuracy of the standard centroid method relative to a low-pass filter approach across cameras and ISO ranges. Localization errors are benchmarked against low-noise ground truth, and their propagation to eSFR results, information capacity, and SNRi metrics is quantified. Findings show that centroid fitting introduces angular bias under noise, leading to blurrier effective responses, while low-pass filtering maintains robust accuracy. These results highlight an underexplored source of error in standards-based image quality analysis and provide a foundation for improved methods. The approach will be extended toward matched filtering, enabling a closer alignment between edge analysis, information-theoretic models, and emerging metrics such as those in ISO 23654 (Digital Imaging — Information Metrics).

“Information-based Dynamic Range”
Norman L. Koren
Session: AVM
Date: March 4th
Time: 3:30
Duration: 20 minutes
We present a new approach to measuring camera dynamic range and low-light performance based on C4 information capacity, which is measured directly from ISO 12233-standard 4:1 contrast slanted edges. Our initial technique involves photographing a test chart that contains 4:1 slanted edges over an extremely wide range of exposures, from ½ or ¼ second (where the brighter side of the edge saturates) to 1/2000 or 1/4000 second, where the image appears nearly black, but a noisy edge is still present. The major advantages of this method are

Dynamic range limits are based on an actual performance metric (C4) rather than SNR, which is only one of the factors that contributes to camera performance.
C4 correctly handles performance degradation due to stray light.

We will discuss new techniques, still under development, for facilitating the measurement.

“A method for calculating NIR bandpass-adjusted Optical Densities for better matching common standard test chart specifications.”
Christian Taylor, Amelia Limbocker
Session: AVM
Date: March 4th
Time: 4:30 PM
Duration: 20 minutes
Near-infrared (NIR) imaging is now prevalent in machine vision, automotive, and biomedical applications, but most step-chart definitions were created for visible imaging. Many standards assume visible lighting conditions and only consider IR-blocking, so NIR-sensitive and RGB+NIR cameras are not adequately addressed. This leads to charts whose nominal densities don’t produce results as intended.
Show MoreWe present a camera-matched methodology for designing NIR test charts whose optical densities (ODs) align with the effective bandpass of a specific camera. First, we estimate the camera–illumination–optics bandpass by measuring camera spectral responsivity and the measured illuminant spectrum at the sample plane. Next, we measure transmittance and/or reflectance spectra of candidate chart materials via spectrophotometry and predict their camera-effective ODs as band-integrated log-ratios. We then select step values to meet the target OD values. Validation is performed by imaging the manufactured chart in RAW, applying linearization, and comparing measured image OD to predictions and to a reference spectrophotometer integrated over the same band. The framework supports transmission and reflectance charts, mono and RGB-NIR sensors, and bands spanning ~780–1100 nm. We report a practical design recipe and guidelines for dynamic-range coverage and repeatability, enabling camera-aware NIR chart optimization rather than one-size-fits-all designs.

2025 Sweden Vehicle Electronics Connected Services (VECS) Conference
2025-03-18 08:00 - 2025-03-19 17:00 (America/Denver) | Svenska Mässan (The Swedish Exhibition & Congress Center), Mässans Gata 24, Gothenburg, Sweden
Jonathan Phillips, VP of imaging science, will be presenting at the VECS Conference, which is focused on “Driving the Future of Sustainable Transportation”. Click here for an interview with Jonathan regarding his talk.

Network with 1400+ Senior Executives from leading OEMs, Tier ones, Suppliers, Academia, Start-ups, Transportation Companies, and Cities/Municipalities
Gain in-depth insights and new disruptive knowledge from highly respected international speakers
Hear best practices from leading OEMs such as Volvo Cars, Volvo Group, Scania, BMW, Saab, Group Lotus, among others

If you are attending the conference and would like to meet with Jonathan or would like him to visit your company near Gothenburg, please contact him at Jonathan@imatest.com.
Program Details Sign Up
Featured Talks
Day 1 – March 18
Track 1 – Technical Challenges & Solutions +
14:00 Camera Image Quality in ADAS Systems for the Automotive Industry

Camera Hardware Optimization of Machine Vision Systems
Machine imaging metrics for automotive sensors in ADAS Systems
New International Standards for CMOS image sensors in the Automotive Industry

Jonathan Phillips, VP of Imaging Science, Imatest & Vice-Chair, ISO TC42 IT-10, Secretary, IS&T Board of Directors, U.S.A.
Day 2 – March 19
Track B – AUTONOMOUS SOLUTIONS & ACTIVE SAFETY +
13:10 In-depth session: Camera Image as a ADAS Systems for the Automotive Industry

Optimization of Machine Vision Systems
Machine image in automotive sensors for ADAS Systems
New demand for CMOS image sensors in automotive industry

Jonathan Phillips, VP of Imaging Science, Imatest, U.S.A.

Visit Imatest at the Edmund Optics Solutions Center in Cupertino Feb 6, 2025
2025-02-06 15:00 - 18:00 (America/Los_Angeles) | Edmund Optics Solutions Center, 20380 Town Center Ln unit 172, Cupertino, CA, 95014, United States
After the conclusion of Electronic Imaging 2025, Join Imatest at the Edmund Optics Silicon Valley Solutions Center for an open house that showcases our Imatest products, followed by a happy hour on the afternoon of February 6th. See below for details and to add to your calendar.
Bring your camera that works at up to 50cm working distance, and we can test it.
Imatest staff attending:

Norman Koren, Founder & CTO
Jonathan Phillips, VP of Imaging Science
Thad Baringer, Imaging Science Sales Engineer
Amelia Spooner, Imaging Science Engineer

If you want to attend or have a private meeting, contact sales@imatest.com.
For a private appointment with Edmund Optics, click here and fill out their form.
Edmund Optics Silicon Valley Solutions Center is a facility where you can integrate machine vision cameras from Allied Vision and Teledyne with Edmund Optics lenses and test them on an Imatest test fixture. EO’s application engineers can consult with you about designing the optimal lens for your imaging task.

@edmundoptics Our Silicon Valley Solutions Center can help you solve your imaging problems! We offer free consulting, test spaces, and a loaner library of lenses, cameras, and lights. Come visit us in Cupertino!

Imatest products on display here include the Benchtop Test Stand, LED Lightbox, Spectral Illuminance Color Sensor, ISO 1223 2023 target, VisNIR HDR, high-precision checkerboard targets, and magnetic chart holder mount.
We will also be showcasing some of our current innovations and development, including our ISP/Camera Simulator (ISPsim), which simulates ISP pipelines and aspects of complete camera systems. We will also demonstrate how you can calculate imaging information metrics for your machine vision image quality needs.

EI2025 Short Course: Information metrics for optimizing Machine Vision systems
2025-02-05 15:30 - 17:30 (America/Los_Angeles) | Hyatt Regency San Francisco Airport, 1333 Bayshore Highway, Burlingame, CA, 94010, United States
Description: A new set of metrics based on information theory promises to be superior to traditional MTF (SFR or sharpness) and noise for predicting machine vision system performance. We will introduce the new information metrics, which include Noise Equivalent Quanta (NEQ), camera information capacity, Ideal Observer SNR (SNRi – for the quality of object detection), and Edge location standard deviation (Edge σ – for the quality of edge location). We will cover the background of the new measurements, why they are more directly related to object and edge detection than traditional measurements, how to conveniently obtain them (primarily from standard slanted edge test patterns), how to interpret them, and how to design matched filters for optimum system performance.
Level: Intermediate
Length: 2 hours
Instructor: Norman Koren, founder & CTO Imatest LLC
Prerequisites: Knowledge of basic image quality measurement concepts, especially MTF (SFR) and noise
Benefits:

the history and mathematics of information theory in imaging,
definitions and interpretations of the information metrics, which include camera information capacity, Noise Equivalent Quanta, Ideal Observer SNR (SNRi – a metric for the quality of object detection), and Edge location standard deviation (Edge σ – a metric for the quality of edge location).
How to conveniently obtain the information metrics
the effect of common types of image processing on metrics, including uniform sharpening and lowpass filtering (for noise-reduction), as well as the nonuniform bilateral filtering found in most camera JPEG images,
design of matched filters to optimize SNRi and Edge σ,
progress in correlating the new metrics with machine vision performance and developing ISO 23654

Intended Audience: Engineers who design and analyze cameras and imaging systems for automotive, medical, security applications, and more
Format: Lecture Primarily lecture, but about 1/4 to 1/3 of the time will be demonstrations
Key Words: MTF, information capacity, Artificial intelligence, machine vision.
Registration is open – Click Here to register
Electronic Imaging 2025, held February 2–6 at the Hyatt Regency San Francisco Airport, offers a vibrant platform for industry and academia to advance imaging technologies. The event features plenary talks, keynotes, technical sessions, networking opportunities, an industry exhibit, and a short course program, covering all aspects of electronic imaging in a dynamic and collaborative environment.
Learn more about Electronic Imaging 2025
If you have any questions, please contact info-metrics@imatest.com.

Electronic Imaging 2025
2025-02-02 08:00 - 2025-02-06 17:00 (America/Denver) | Hyatt Regency San Francisco Airport, 1333 Bayshore Highway, Burlingame, CA, 94010, United States
Imatest attended Electronic Imaging 2025 in Burlingame CA.

Featured Talk:
Megan Borek “Improving Image Equity: Representing the diversity of skin tones in photographic test charts for digital camera characterization” (4391)
Session: Skin Tone Capture and Image Quality I
Date: 2/5/2025 (Wednesday)
Time: 11:00 AM – 12:30 PM (Pacific Time)
Duration: 20 minutes

Featured Short Course:
Norman Koren: Information Metrics for Optimizing Machine Vision Systems
Date: 2/5/2025 (Wednesday)
Time: 3:30 – 5:30 PM (Pacific Time)
Duration: 2 hours

After the Event:
Open House / Happy Hour at the Edmund Optics Solution Center in Cupertino
Date: 2/6/2025 (Thursday)
Time: 3:00 – 7:00 PM (Pacific Time)
Duration: 4 hours

Visit the Edmund Optics Solutions Center in Cupertino Oct 24 2024
2024-10-24 15:00 - 19:00 (America/Los_Angeles) | Edmund Optics Solutions Center, 20380 Town Center Ln unit 172, Cupertino, CA, 95014, United States
Join Imatest and Edmund Optics in Cupertino at the Edmund Optics Silicon Valley Solutions Center. This is a facility where you can integrate machine vision cameras from Allied Vision and Teledyne with Edmund Optics lenses and test them on an Imatest test fixture. EO’s application engineers can consult with you about designing the optimal lens for your imaging task.

@edmundoptics Our Silicon Valley Solutions Center can help you solve your imaging problems! We offer free consulting, test spaces, and a loaner library of lenses, cameras, and lights. Come visit us in Cupertino!

Imatest products on display here include the Benchtop Test Stand, LED Lightbox, Spectral Illuminance Color Sensor, ISO 1223 2023 target, VisNIR HDR, high-precision checkerboard targets, and magnetic chart holder mount.
Join us for an open house, followed by a happy hour on the afternoon of October 24th. See below for links to add to your calendar.
For a private meeting with Imatest Imaging Science Engineer Ian Longton and Chief Product Officer Christian M Taylor on Oct 24 or 25, contact sales@imatest.com.
For a private appointment with Edmund Optics click here and fill out their form.

Asia/Americas Office Hour: Correlating image quality with machine vision performance
2024-10-23 19:00 - 20:00 (America/Denver) | Zoom Office Hour Asia/Americas
The task of computer vision (CV) involves analyzing a stream of images from an imaging device. Some simple applications, such as object counting, may be less dependent on good camera quality. But for more advanced CV applications with limited control of lighting & distance, the quality of your overall vision system will depend on the quality of your camera system. This is increasingly important when an error made by the vision system could lead to a decision that impacts safety. Along with proper optimization of a CV model, ensuring that that model is fed by imagery from a high-quality camera system is critical to maximizing your system’s performance.
Office hours include selected topics but are not limited to them. Ask any questions you like when you register or during the call. We’ll try to answer all questions that are submitted if time allows. Office hours are usually held on the third Wednesday of each month at 11:00 am MT for Europe and the Americas and the fourth Wednesday at 7:00 pm MT (9:00 am the next day in China) for Asia and the Americas. View the schedule of upcoming office hours here.

Click here to register for the Office Hour
Related Links

Correlating the Performance of Computer Vision Algorithms with Objective Image Quality Metrics
Image information metrics: Information Capacity and More

Europe/Americas Office Hour: Correlating image quality with machine vision performance
2024-10-16 11:00 - 12:00 (America/Denver) | Zoom Office Hour Europe/Americas

Imatest Presented at AutoSens Europe 2024
2024-10-08 10:00 - 2024-10-10 16:45 (Europe/Berlin) | Palau De Congressos Barcelona, Avda. Diagonal, 661*671, Barcelona, Les Corts, 08028, Spain
Imatest attended AutoSens Europe on October 8-10, 2024 in Barcelona, Spain. We presented our advanced testing methods and algorithms for validating the quality of automotive cameras.
Watch On Demand AutoSens Europe Website
Virtually Visit Imatest’s Booth

Related Products
Calibrated Reference Camera for Camera Monitor System (CMS) testing with Leader SFR-Fit
Leader SFR-Fit MTF Measurement Software
Imatest Spectral Illuminance Color Sensor
SFRreg Field Ruggedized Target
ISO 12233 Edge SFR (eSFR) Inkjet chart
Event Photos

Tutorial by Norman Koren

Information Metrics for Performance and Optimization of Machine Vision Systems.
Norman Koren
Founder / CTO
We discuss the mathematical background and practical measurement techniques for a new set of image quality metrics that promise to be superior to MTF (sharpness) and noise as predictors of machine vision performance. The new metrics include Noise Equivalent Quanta (NEQ), Ideal Observer SNR (SNRi), and Edge location standard deviation (Edge σ). They can be measured from slanted edges as well as Siemens star and dead leaves (spilled coins) test chart images.¬ We cover

the origin and significance of information capacity, and its use as a fundamental metric for qualifying cameras,
the effect on measurements of common types of image processing, especially the bilateral filters found in most JPEG images,
the distinction between total information capacity and information capacity for contrast-limited patterns (typically 4:1 or 60% Michelson contrast slanted edges), which can be measured for a wide range of exposures,
obtaining the metrics for object detection (SNRi) and the object location (Edge σ),
the effects of sharpening and lowpass (noise-reduction) filtering, showing how excessive sharpening degrades performance,
design of matched filters to optimize SNRi and Edge σ for specific tasks, and tradeoffs for multiple tasks
progress in correlating the new metrics with standard machine vison performance metrics, such as Mean Average Precision (mAP) and Intersection over Union (IoU), which are related to object detection and location.

See also Image Information Metrics.
Visit Imatest’s Booth #334 for Demonstrations

Leader SFR-Fit camera resolution measurement software measures MTF (Modulation Transfer Function). MTF indicates spatial frequency characteristics using multiple distortion and uniformity-corrected sine patterns that can be presented across one or more displays.
Conventional MTF measurement methods can have issues with black box camera systems that prevent the acquisition of the RAW or minimally processed image. If these systems have sharpening enabled, slanted edges can overstate MTF, especially at high frequencies.
The SFR-Fit measurement system can produce highly accurate measurements of automotive cameras is compatible with ultra-wide-angle lenses.
Calibrated Reference Camera for Camera Monitor System (CMS) testing with Leader SFR-Fit
By using SFR-Fit Ver2.4 and a calibrated reference camera, you can measure the MTF of a CMS electronic mirror.

SFRreg Field Ruggedized Target

Watch On Demand
Previous Event: AutoSens USA 2024
