No offerings have been identified for this subject in 2016

ITC368 Image Processing and Analysis (8)


This subject builds on the students' previous knowledge of C++ programming at a high level. It provides a study of fundamental knowledge and practical techniques for digital manipulation of images, including image enhancement and restoration, edge detection and segmentation, feature extraction and description, object understanding and recognition. It also provides the study of image processing techniques used in Computer Vision and GIS applications.

+ Subject Availability Modes and Location

Continuing students should consult the SAL for current offering details prior to contacting their course coordinator: ITC368
Where differences exist between the handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject information

Duration Grading System School:
One sessionHD/FLSchool of Computing and Mathematics

Assumed Knowledge

ITC140 and MTH219

Enrolment restrictions

Available to students enrolled in the courses of Bachelor of Computer Science, Bachelor of Computer Science (Games Technology) and Bachelor of Computer Science (Games Technology)(Honours). Also available to students with programming background in other courses under the approval of subject coordinator.

Learning Outcomes

Upon successful completion of this subject, students should:
* be able to identify a variety of image processing techniques
* be able to explain the purpose of each process and underlying principles
* be able to select appropriate image processing and analysis techniques to
achieve predetermined objectives in application areas
* be able to implement well-defined new methods for image processing and
analysis with the use of C++ programming language
* be able to integrate image processing and analysis techniques into
applications of remote sensing and GIS system


The subject will cover the following topics:
* Introduction and overview of image processing, image acquisition, and digital color image formats * CImg C++ image processing library * Histogram processing and Enhancement: contrast stretching and spatial filtering * Image restoration with both spatial and frequency filtering * Edge detection and segmentation: Region-based methods and contours * Texture analysis: Statistical and spectral approaches * Features extraction: Use of Scale-Invariant Feature Transform (SIFT) * Object recognition with SIFT features and K-means clustering * Examples of image processing in Computer Vision and GIS applications


The information contained in the 2016 CSU Handbook was accurate at the date of publication: 06 September 2016. The University reserves the right to vary the information at any time without notice.