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DTSTART;TZID=America/Los_Angeles:20260301T140000
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DTSTAMP:20260409T031809
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UID:10000012-1772373600-1772384400@www.imatest.com
SUMMARY:EI2026 Short Course: Camera Simulation for Predicting Information Metrics and Machine Vision Performance
DESCRIPTION:Instructor: Norman L. Koren\nWhen: Sunday\, March 1st 2:00 PM – 5:00 PM PST \nBenefits: \n\nUnderstand the fundamentals of information capacity and how it relates to conventional SFR and noise measurements\,\nUnderstand the information metrics (information capacity and others derived from information theory)\, and learn how they relate to system performance\,\nLearn 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)\,\nLearn how to determine the effects of each system component or image processing step on the system performance.\n\nCourse description: \nThis 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.  \nNext\, the course describes the camera performance simulator\, including \n\nCreating input images (usually test targets)\,\nSimulating lens degradations\,\nModeling the image sensor noise and ISP (Image Signal Processing)\,\nDisplaying results\, including the standard performance metrics and new information metrics.\n\nThis 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.\n \nIntended 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. \n \nNorman 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. \nEI2026 Details Registration 
URL:https://www.imatest.com/event/ei2026-short-course-camera-simulation-info-metrics/
LOCATION:Hyatt Regency San Francisco Airport\, 1333 Bayshore Highway\, Burlingame\, CA\, 94010\, United States
CATEGORIES:Training Course
ATTACH;FMTTYPE=image/png:https://www.imatest.com/wp-content/uploads/2025/12/shortcourse_2026_teaser.png
ORGANIZER;CN="IS&T%3A Society for Imaging Science and Technology":MAILTO:ei@imaging.org
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DTSTART;TZID=America/Los_Angeles:20250205T153000
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CREATED:20241024T192849Z
LAST-MODIFIED:20241114T130349Z
UID:10000006-1738769400-1738776600@www.imatest.com
SUMMARY:EI2025 Short Course: Information metrics for optimizing Machine Vision systems
DESCRIPTION: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. \nLevel: Intermediate \nLength: 2 hours \nInstructor: Norman Koren\, founder & CTO Imatest LLC \nPrerequisites: Knowledge of basic image quality measurement concepts\, especially MTF (SFR) and noise \nBenefits: \n\nthe history and mathematics of information theory in imaging\,\ndefinitions 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).\nHow to conveniently obtain the information metrics\nthe 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\,\ndesign of matched filters to optimize SNRi and Edge σ\,\nprogress in correlating the new metrics with machine vision performance and developing ISO 23654\n\nIntended Audience: Engineers who design and analyze cameras and imaging systems for automotive\, medical\, security applications\, and more \nFormat: Lecture Primarily lecture\, but about 1/4 to 1/3 of the time will be demonstrations \nKey Words: MTF\, information capacity\, Artificial intelligence\, machine vision. \nRegistration is open – Click Here to register \nElectronic 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. \nLearn more about Electronic Imaging 2025 \nIf you have any questions\, please contact info-metrics@imatest.com.
URL:https://www.imatest.com/event/ei2025-short-course-information-metrics-for-optimizing-machine-vision-systems/
LOCATION:Hyatt Regency San Francisco Airport\, 1333 Bayshore Highway\, Burlingame\, CA\, 94010\, United States
CATEGORIES:Training Course
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ORGANIZER;CN="IS&T%3A Society for Imaging Science and Technology":MAILTO:ei@imaging.org
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