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Apr 24, 2024
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EE 587 - Machine Vision3 lecture hours 0 lab hours 3 credits
Course Description
This course introduces the student to machine vision technology and its applications. Topics include lighting equipments and techniques, image acquisition devices/systems and techniques, and image processing techniques. Interfacing machine vision systems to other engineering systems are also discussed. Laboratory experiments and a class project include introduction to various kinds of vision systems, image processing techniques, and applications. (prereq: Senior standing in EE or CE)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• Describe and apply the fundamental concepts of machine vision systems.
• Describe and apply the principles underlying the application of machine vision systems.
• Describe a variety of machine vision applications.
• Describe the application of machine vision systems to industrial processes.
• Write concise, professional technical reports
Prerequisites by Topic
• Knowledge of a programming language.
• Knowledge of basics of physical science.
• Understanding of manufacturing processes.
Course Topics
• Introduction to machine vision, image sensing fundamentals, relationship to other disciplines. (2 classes)
• Optics and lighting: fundamentals, practical light sources, imaging by lensing. (2 classes)
• Cameras and sensors: rectangular and linear arrays, CCD sensor architectures. (3 classes)
• Image processors and algorithms: windowing (generalized areas of interest), Sobel operator histograms, SRI algorithms. (4 classes)
• Discussion of term paper requirements, one-hour exam. (3 classes)
• Inspection case studies - examples, pistons, disk brakes, dishes, light bulbs, very high speed bottle inspection in packaging lines. (4 classes)
• Perspective projective and pinhole camera models, world coordinates and transformations. (2 classes)
Coordinator
Hue Tran
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