Image Processing TMUL 3306

Course description:

This course presents fundamental concepts in image processing. Topics may include properties of digital images, digital image formats, image acquisition devices, edge detection, convolution ?ltering, image segmentation, shape representation, image compression, image morphology, spectral analysis, texture, object recognition, motion analysis and 3D interpretation. The course is primarily meant to develop on-hand experience in applying these tools to process these images. Hence the programming assignments form a key component of this course.  The students would be encouraged to develop the image processing tools from scratch, rather than using any image processing library functions.

Course Aims:

This course aims to enable the student to:
  • Identify all the types and characteristics of the image. 
  • Learn about different methods of digital image processing.
  • Understand the typical steps for solution of image processing/vision problems: pre-processing, segmentation, description, and recognition. 
  • Learn mechanisms to increase the resolution of images.
  • Learn different methods to remove the noise on images.
  • Use different techniques to segment images.
  • Learn the mechanisms of image compression. 
  • Use  edge detection technique.

Course outcomes:

Upon completion of the course, students should be able to: 
  • Review the fundamental concepts of a digital image processing system. 
  • Analyze images in the frequency domain using various transforms. 
  • Evaluate the techniques for image enhancement and image restoration. 
  • Categorize various compression techniques. 
  • Interpret image segmentation and representation techniques. Write a program which implements fundamental image processing algorithms. 
  • Be conversant with the mathematical description of image processing techniques and know how to go from the equations to code.
  • choose appropriate methods and implement solutions to small-scale image processing and vision problems.