dc.contributor.advisor | Chi-Ren, Shyu | eng |
dc.contributor.author | Klaric, Matthew | eng |
dc.date.issued | 2010 | eng |
dc.date.submitted | 2010 Fall | eng |
dc.description.abstract | In recent years we have seen the development of several novel content-based retrieval (CBR) systems that have had success by focusing on a specific domain and exploiting domain-speci c information. CBR systems allow users to query a media database using item content as opposed submitting a text-based query. In many CBR applications, the input to the search process is a complicated object that may be composed of several constituent parts. The proposed approach performs CBR queries by decomposing a complex query into several heterogeneous queries. We have developed a multi-index, multi-object CBR framework for geospatial imagery retrieval that extracts features specifically developed for high-resolution commercial satellite imagery. The results of these queries will be spatially summarized for a user based on both retrieval score and spatial distance. This allows results to be presented in a logical manner to allow for more efficient interpretation by the user. Further, we propose to develop an additional search capability that allows for multi-object searches by spatial configuration rather than simply by object-to-object correspondence. Additionally, to confront situations where a user has determined that certain search results are not relevant, we will provide online and memory-based relevance feedback algorithms for use with multi-index, multi-object CBR systems. The experimental results demonstrate the efficiency and accuracy of the proposed methods; moreover, through the fusion of multi-index and multi-object search techniques, we are able to construct new, sophisticated query mechanisms. | eng |
dc.format.extent | xii, 120 pages | eng |
dc.identifier.uri | https://hdl.handle.net/10355/41907 | |
dc.identifier.uri | https://doi.org/10.32469/10355/41907 | eng |
dc.language | English | eng |
dc.publisher | University of Missouri--Columbia | eng |
dc.relation.ispartofcommunity | University of Missouri--Columbia. Graduate School. Theses and Dissertations | eng |
dc.rights | OpenAccess. | eng |
dc.rights.license | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License. | |
dc.subject | Content-based retrieval | eng |
dc.subject | Satellite imagery | eng |
dc.subject | Multi-index searching | eng |
dc.subject.FAST | Content-based image retrieval | eng |
dc.subject.FAST | Image processing -- Digital techniques | eng |
dc.subject.FAST | Database management -- Computer programs | eng |
dc.title | Multi-index, multi-object content-based retrieval with spatial summarization | eng |
dc.type | Thesis | eng |
thesis.degree.discipline | Computer science (MU) | eng |
thesis.degree.grantor | University of Missouri--Columbia | eng |
thesis.degree.level | Doctoral | eng |
thesis.degree.name | Ph. D. | eng |