VISUAL INFORMATION SYSTEMS
Credit points: 15
This subject covers an overview of visual information access, image representation, feature extraction, image recognition and understanding, and content-based image retrieval techniques. Design issues on content-based image retrieval systems for image database management will be addressed, which contain image feature extraction, indexing, similarity measure, lower-bounding lemma and performance evaluation. Practice on design of image recognition systems (IRS) or content-based image retrieval (CBIR) systems will be offered in Labs. Knowledge on HTML, PHP, and MySQL will be needed to implement these systems.
FacultyFaculty of Science, Tech & Engineering
Subject Co-ordinatorJustin Wang
Available to Study Abroad StudentsYes
Subject year levelYear Level 3 - UG
Incompatible subjects CSE31MS, CSE32MS, CSE41FMS, CSE42FMS, CSE3MS, CSE4FMS, CSE3IMS
|Resource Type||Title||Resource Requirement||Author and Year||Publisher|
|Readings||Content-based image and video retrieval||Recommended||Marques, O and Furht, B 2002||1ST ED, SPRINGER|
|Readings||Image recognition and classification: algorithms, systems and applications||Recommended||Javidi, B 2002||1ST EN, CRC PRESS|
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Melbourne, 2014, Semester 1, Day
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorJustin Wang
One 2.0 hours laboratory class per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.
One 2.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
|one 3-hour examination||60|
|second assignment (group-based) with oral presentation||Hurdle requirement: In order to pass the unit, students must obtain an overall pass grade, pass the examination and pass the overall non-examination components.||20|
|the first assignment with approximate 750 words report||20|