Introduction to image processing
Dr Michael Morgan
4 points * Two 1-hour lectures and one 2-hour laboratory class per week plus six 1-hour tutorials * First semester * Clayton * Prerequisites: Nil, but CSC1011 or CSC1030 or PHS1011 or PHS1031 is highly recommended * Prohibition: CSC3140, GPS2012
Objectives On successfully completing this subject a student should have a working knowledge of digital image processing and the representation of digital data; be able to implement image processing operations to improve the quality of an image; understand the discrete convolution process and spatial filtering; be familiar with methods of representing data in the Fourier domain through the DFT; understand the processes of image segmentation, in particular texture segmentation; be able to apply image processing to selected areas of science, technology and medicine.
Synopsis Point operations: the gray scale histogram (GSH), thresholding, contrast operations, GSH equalisation, LUTs, pseudo-colouring. One-dimensional and two-dimensional spatial operations: discrete convolutions and spatial filtering. One-dimensional and two-dimensional Fourier transforms: the DFT and FFT. The discrete cosine transform. Introduction to other transforms. Image segmentation, feature extraction and pattern recognition. Texture analysis: Laws masks and texture segmentation, statistical models of texture analysis, co-occurrence matrices. Exact and approximate data coding and compression techniques.
Assessment Examination (2 hours): 50% * Laboratory work: 50%
Prescribed texts
Gonzalez R C and Woods R E Digital image processing 3rd edn, Addison-Wesley, 1992
| Published by Monash University, Clayton, Victoria
3168 Copyright © Monash University 1996 - All Rights Reserved - Caution Authorised by the Academic Registrar December 1996 |