Availabilities:

LocationDomesticInternational
Gold Coast

Unit description

Focuses on computer vision methods and techniques in contemporary expert/intelligent systems. Students will learn various image pre-processing, feature extraction, segmentation and classification algorithms and apply them to solve real-world computer vision problems. This unit provides students with in-depth understanding of computer vision and artificial intelligence technologies behind contemporary expert/intelligent systems.

Unit content

1. Introduction to image processing and computer vision

2. Image pre-processing techniques

3. Feature extraction methods

4. Object detection and classification

5. Image segmentation

6. Computer vision systems in smart environments

Learning outcomes

Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes. The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.

On completion of this unit, students should be able to:
1analyse and apply appropriate image pre-processing algorithms to a real-world image processing/pattern recognition problem.
2develop and apply suitable feature extraction methods to characterise images.
3implement appropriate object detection and classification techniques.
4build image segmentation and classification solutions.

On completion of this unit, students should be able to:

  1. analyse and apply appropriate image pre-processing algorithms to a real-world image processing/pattern recognition problem.
  2. develop and apply suitable feature extraction methods to characterise images.
  3. implement appropriate object detection and classification techniques.
  4. build image segmentation and classification solutions.

Prescribed Learning Resources

Prescribed Texts
  • No prescribed texts.
Prescribed Resources/Equipment
  • Anaconda, Python and related libraries, such as openCV

Prescribed Learning Resources may change in future Teaching Periods

Teaching and assessment

Teaching method
Workshop 1 hour (Weekly)
Tutorial 2 hours (Weekly)
Assessment
Project30%
Project60%
Short written response10%
Notice

Intensive offerings may or may not be scheduled in every teaching period. Please refer to the timetable for further details.

Southern Cross University employs different teaching methods within units to provide students with the flexibility to choose the mode of learning that best suits them. SCU academics strive to use the latest approaches and, as a result, the learning modes and materials may change. The most current information regarding a unit will be provided to enrolled students at the beginning of the teaching period.

Fee information

Domestic

Commonwealth Supported courses
For information regarding Student Contribution Amounts please visit the Student Contribution Amounts.

Fee paying courses
For postgraduate or undergraduate full fee paying courses please check Domestic Postgraduate Fees OR Domestic Undergraduate Fees

International

Please check the international course and fee list to determine the relevant fees.

+