Overview

Topic status: We're looking for students to study this topic.

A Content-Based Image Retrieval (CBIR) system is a computer-based system for searching and retrieving images from massive digital image databases. Image retrieval systems use visual features for classification and retrieval of images.  Usually a user provides an example image to the system and the system searches the database and return desirable images to the users. Content-based image retrieval has been one of the most vivid research areas over the last two decades.

Soft computing consists of set of technologies: fuzzy logic/rough set, neural computing, evolutionary computation, machine learning and probabilistic reasoning. Due to their strong learning and cognitive ability and good tolerance of uncertainty and imprecision, soft computing techniques have found wide applications. Image processing and retrieval is one of such applications.

This research aims to develop an effective method for image retrieval by integrating rough set (or fuzzy set) theory with machine learning approaches. The expected outcomes of this project include new approaches for image retrieval and an efficient and effective image retrieval prototype system.

Applicants with computer science, information science or engineering, especially with signal processing background, are welcome to contact the supervisor directly.

Jinglan believes that bright people can learn quickly. If you are interested but do not have the background, please contact the supervisor directly to see if there are any pathways available.
Study level
PhD, Masters, Honours
Supervisors
QUT
Organisational unit

Science and Engineering Faculty

Research areas
Keywords
Image searching, Artificial intelligence
Contact
Please contact the supervisor for enquiries.