Instructor: Norman Koren, Imatest LLC
Level: Intermediate
Prerequisites: Undergraduate probablility

Benefits:
This course enables the attendee to: Learn how to use the new information-based metrics to predict and optimize machine vision system performance.

Course 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. The course introduces 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). It covers 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. Material covered includes:

• 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 vison performance and developing ISO 23654.

Intended Audience: Engineers who design and analyze cameras and imaging systems for automotive, medical, security applications, and more.

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.