Lower-Level and Higher-Level Approaches to Content-Based Image Retrieval

This paper describes a content-based image retrieval system that employs both higher-level and lower-level vision methodologies separately and in conjunction for the retrieval of images containing large manmade objects. The goal is to use the lower-level analysis module to increase the capability of the higher-level analysis module, for queries where the structure exhibited by the manmade objects is important. Higher-level analysis is performed globally to extract structure by employing the elements of perceptual grouping to extract different shape representations for higher-level feature extraction from primitive image features. The shape representations include “L” junctions, “U” junctions and parallel groups. Lower-level analysis is performed globally by using Gabor filters to extract texture features. A manmade object region of interest extracted by using perceptual grouping is used as a frame for conducting lower-level analysis. Lower-level analysis may be performed wit...

• Type: Conference
• Year: 2000
• Where: SSIAI
• Authors: Qasim Iqbal, Jake K. Aggarwal
• Keywords: Image Analysis, Lower-level Analysis, Lower-level Analysis Module, Manmade Object, SSIAI 2000