IMAGE RETRIEVAL

CSE5IR

2021

Credit points: 15

Subject outline

The explosive growth of digital media data has imposed unprecedented challenges for big multimedia data computing and management. In this subject, you will be introduced to a broad range concepts in image computing and retrieval for multimedia database management. You will learn and apply both the basics of digital image computing. Cutting-edge techniques for multimedia data understanding, content analysis, and image retrieval are practiced, applied, and discussed. With learnt knowledge and techniques, you have the skills to implement an image retrieval model.

SchoolEngineering and Mathematical Sciences

Credit points15

Subject Co-ordinatorLydia Cui

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 5 - Masters

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

PrerequisitesCSE5ML OR CSE3CI OR CSE5CI

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

Multimedia Information Retrieval and Management Technological Fundamentals and Applications

Resource TypeBook

Resource RequirementRecommended

AuthorD. Feng, W.C.Siu, and H.J.Zhang

Year2003

Edition/Volume2nd ED

PublisherChapman and Hall/ CRC

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/Volume4th edition

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

01. Apply image enhancement and representation techniques.
02. Implement critical components in content-based image retrieval systems and explain design issues by learnt image processing and analytics techniques for feature extraction, similarity measurement and indexing.
03. Design, implement and evaluate an image retrieval system with learned knowledge and techniques.
04. Research and explain the significance of robust image retrieval techniques for real-world applications.

Subject options

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Start date between: and    Key dates

Melbourne (Bundoora), 2021, 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 elementCommentsCategoryContributionHurdle% ILO*

Assignment 1 - Design and implementation of an image retrieval model (1500 words equivalent)

N/AAssignmentIndividualNo35 SILO2, SILO3, SILO4

Assignment 2 - Presentation of designed image retrieval model (1000 words equivalent)

N/AAssignmentIndividualNo15 SILO4

One 2-hour exam (2000 words equivalent)

N/ACentral examIndividualNo50 SILO1, SILO2