Credit points: 15
This subject covers both fundamentals of image processing as well as computing techniques with applications in many cutting-edge domains such as image recognition, object detection and segmentation, image registration and retrieval. Design issues on image recognition will be addressed, which contain eigenface technology, image feature extraction, similarity measurement, and performance evaluation. Practice on image recognition will be offered in Labs.
SchoolEngineering and Mathematical Sciences
Subject Co-ordinatorLydia Cui
Available to Study Abroad/Exchange StudentsYes
Subject year levelYear Level 3 - UG
Available as ElectiveNo
Quota Management StrategyN/A
Quota-conditions or rulesN/A
Minimum credit point requirementN/A
Pattern Recognition and Machine Learning
AuthorChristopher M. Bishop
Digital Image Processing
AuthorRafael C. Gonzalez, Richard E. Woods.
Self sourced or Uni sourcedN/A
Entire subject or partial subjectN/A
Total hours/days requiredN/A
Location of WBL activity (region)N/A
WBL addtional requirementsN/A
Graduate capabilities & intended learning outcomes
Intended Learning Outcomes
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Melbourne (Bundoora), 2021, Semester 1, Day
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorLydia Cui
Laboratory ClassWeek: 11 - 22
One 2.00 hours laboratory class per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.
LectureWeek: 10 - 22
One 2.00 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Final centrally scheduled exam (online quiz via LMS) (2 Hours) (equivalent to 2100 words)
|Central exam||Individual||Yes||70||SILO1, SILO2|
Design report (equivalent to 1200 words)