IMAGE PROCESSING

CSE4VIS

Not currently offered

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 measure, and performance evaluation. Practice on image recognition will be offered in Labs. .

SchoolEngineering and Mathematical Sciences

Credit points15

Subject Co-ordinatorLydia Cui

Available to Study Abroad/Exchange StudentsYes

Subject year levelYear Level 4 - UG/Hons/1st Yr PG

Available as ElectiveNo

Learning ActivitiesN/A

Capstone subjectNo

Subject particulars

Subject rules

Prerequisites CSE2AIF or admission into one of the following courses: SMIT, SMICT, SMITCN, SMCSC, SGIT or SGCS

Co-requisitesN/A

Incompatible subjects CSE3VIS AND Students in the following courses are not permitted to enrol: SBCS, SBIT, SBITP and SBBIY

Equivalent subjectsN/A

Quota Management StrategyN/A

Quota-conditions or rulesN/A

Special conditionsN/A

Minimum credit point requirementN/A

Assumed knowledgeN/A

Readings

Digital Image Processing

Resource TypeRecommended

Resource RequirementN/A

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

Pattern Recognition and Machine Learning

Resource TypeRecommended

Resource RequirementN/A

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

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. Demonstrate understanding of image processing fundamentals by being able to explain data sampling and quantization in acquisition, image enhancement and denoising, and image representation.
02. Demonstrate knowledge of major components and issues in image processing applications by being able to describe learned image processing and pattern recognition techniques for image recognition, object detection and segmentation, image registration and retrieval.
03. Implement and evaluate an image recognition system with learned knowledge and techniques.
04. Research and explain the significance of robust image recognition techniques for real applications.

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