May 04, 2024  
2014-2015 Undergraduate Academic Catalog 
    
Catalog Navigation
  Catalog Home
  President’s Welcome
  Academic Calendar
  University Overview
  Enrollment Management Department
  Graduate and Professional Education
  Academic Regulations and Policies
  Student Accounts, Fees and Financial Aid
  Other Academic Resources
  Academic Departments, Undergraduate Degree Programs, Minors and Certificates
  Degree Programs, Minors and Certificates
  Two-degree Programs
  Graduate Studies Programs
  Reserve Officer Training Corps (ROTC)
  Course Descriptions
  Board of Regents, Academic Administration, Faculty and Advisory Committees
  Campus Map
  My Portfolio
HELP
2014-2015 Undergraduate Academic Catalog [ARCHIVED CATALOG]

Facebook this Page (opens a new window)
Tweet this Page (opens a new window)
Add to Portfolio (opens a new window)

EE 487 - Machine Vision

3 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)
Laboratory Topics
• Students use the ITEX system to acquire images and measure the effect of f-stop changes on pixel intensity. They also learn basic software commands for the ITEX system.
• The second laboratory makes use of the OPCON linear array camera and processor. The camera field of view is computed and recorded, and a histogram of an edge is generated.
• Using the ITEX systems, students design and implement a program which inspects an object of their choice.
Coordinator
Hue Tran


Facebook this Page (opens a new window)
Tweet this Page (opens a new window)
Add to Portfolio (opens a new window)