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COURSE NUMBER: CMPT 450
COURSE TITLE: Image Processing and Embedded Images
NAME OF INSTRUCTOR: Dr. Michael Janzen
CREDIT WEIGHT AND WEEKLY TIME DISTRIBUTION: credits 3(hrs lect 3 - hrs sem 0 - hrs lab 3)
COURSE DESCRIPTION: This course introduces the topic of image processing, including a mathematical approach to understanding the technical aspect of how an image can be created, viewed and modified. Utilizing an image processing toolbox various images will be analyzed using standard algorithms, noisy or degraded images restored and enhanced for improved intelligibility, shapes and textures will be analyzed, and features of images will be embedded or extracted.

Prerequisites: CMPT 305
REQUIRED TEXTS:
  • Gonzalez, Rafael C; Woods Richard E.; Eddins (2007), Digital Image Processing 3rd ed., Pearson.
  • The following may be useful.  If desired these books can be put on reserve in the King’s library.
    • Sonka, Milan; Hlavac, Vaclav; Boyle, Roger (2008), Image processing, analysis and machine vision, Thompson Learning.
    • Gonzalez, Rafael C; Woods Richard E.; Eddins, Steven L. (2009), Digital image processing using MATLAB, Gatesmark Publishing.
    • Russ, John C. (2011) The image processing handbook 6 th  ed., CRC Press.  
  • Also see the paper reading list for discussion group papers.
MARK DISTRIBUTION IN PERCENT:
Laboratory Work 5%
Lecture Assignments 28%
Paper/Group discussion 13%
Proposal3%
Project8%
Presentation3%
Midterm 15%
Final Exam 30%
100%
COURSE OBJECTIVES: This course is intended to introduce students to image processing.  By the end of this course a student should be able to
  • Understand what makes an image and how an image is stored
  • Process an image using several techniques including grey scaling an image, convolutions, operations on black and white images, and some image classification techniques
  • Have introductory GPGPU skills
  • Discuss issues concerning image processing in society
COURSE OUTLINE:
  • What is an Image?
  • Greyscale and Black & White operations
  • Convolutions
  • GPGPU processing
  • Image resizing
  • Image formats and compression
  • Background subtraction techniques
  • Textures in Images
  • Image Classification
  • Additional topics as time allows


Required texts, assignments, and grade distributions may vary from one offering of this course to the next. Please consult the course instructor for up to date details.

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