Date of Award


Publication Type

Master Thesis

Degree Name



Computer Science

First Advisor

Ahmad, Imran (School of Computer Science)


Computer Science.




Multimedia applications involving image retrieval demand fast response, which requires efficient database indexing. Generally, a two-level indexing scheme in an image database can help to reduce the search space against a given query image. The first level is required to significantly reduce the search space for the second-stage of comparisons and must be computationally efficient. It is also required to guarantee that no new false negatives may result. In this thesis, we propose a new image signature representation for the first level of a two-level image indexing scheme that is based on hierarchical decomposition of image space into spatial arrangement of image features (quadtrees). We also formally prove that the proposed signature representation scheme not only results in fewer number of matching signatures but also does not result in any new false negative. Further, the performance of the retrieval scheme with proposed ignature representation is evaluated for various feature point detection algorithms.