cse3vis image processing
IMAGE PROCESSING
CSE3VIS
2020
Credit points: 15
Subject outline
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 (Pre 2022)
Credit points15
Subject Co-ordinatorLydia Cui
Available to Study Abroad/Exchange StudentsYes
Subject year levelYear Level 3 - UG
Available as ElectiveNo
Learning ActivitiesN/A
Capstone subjectNo
Subject particulars
Subject rules
PrerequisitesCSE2AIF
Co-requisitesN/A
Incompatible subjectsN/A
Equivalent subjectsN/A
Quota Management StrategyN/A
Quota-conditions or rulesN/A
Special conditionsN/A
Minimum credit point requirementN/A
Assumed knowledgeN/A
Learning resources
Pattern Recognition and Machine Learning
Resource TypeBook
Resource RequirementRecommended
AuthorChristopher M. Bishop
Year2006
Edition/VolumeN/A
PublisherSpringer
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Digital Image Processing
Resource TypeBook
Resource RequirementRecommended
AuthorRafael C. Gonzalez, Richard E. Woods.
Year2017
Edition/VolumeN/A
PublisherPearson
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Career Ready
Career-focusedNo
Work-based learningNo
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
Graduate Capabilities
Intended Learning Outcomes
Subject options
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Melbourne (Bundoora), 2020, Semester 1, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorLydia Cui
Class requirements
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.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | ILO* |
|---|---|---|---|---|---|
One 3-hour examination (equivalent to 3,000 words)Hurdle requirement: To pass the subject, a pass in the examination is mandatory. | N/A | N/A | Yes | 70 | SILO1, SILO2 |
Design report (equivalent to 1200 words) | N/A | N/A | No | 30 | SILO3, SILO4 |