Lower-Level and Higher-Level Vision Approaches for Content-Based Image Retrieval

Mr. Qasim Iqbal

Electrical and Computer Engineering
The University of Texas at Austin

Friday, March 23rd, 3:00 PM, ENS 302

qasim@ece.utexas.edu

Abstract

The interest in automatic analysis of images based upon their content has increased with recent developments in the Web (WWW), digital image collections, networking and multimedia. Active research in content-based image retrieval is geared towards the development of methodologies for analyzing, interpreting, cataloging and indexing image databases.

This talk will focus on an image retrieval system developed at UT Austin, which is based upon a combination of lower-level and higher-level vision principles. Lower-level analysis employs a channel energy model to describe image texture and utilizes color histogram techniques. Gabor filters are used to extract fractional energies in various spatial-frequency channels. Higher-level analysis uses perceptual inference and grouping principles to extract semantic information describing the structural content of an image. The system is able to serve queries ranging from scenes of purely natural objects such as vegetation, trees and sky, to images containing conspicuous structural objects such as buildings, towers and bridges.

Biography

Qasim Iqbal is a graduate student under the direction of Prof. J. K. Aggarwal in the Department of Electrical and Computer Engineering at The University of Texas at Austin. He obtained his B.Sc. in Electrical Engineering from the University of Engineering and Technology, Lahore, Pakistan, in 1995, and M.S. in Electrical Engineering from The University of Texas at Austin in 1998. He is currently pursuing a Ph.D.E.E. degree in area of computer vision.

A list of Telecommunications and Signal Processing Seminars is available at from the ECE department Web pages under "Seminars". The Web address for the Telecommunications and Signal Processing Seminars is http://anchovy.ece.utexas.edu/seminars