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Proceedings Paper

Manchester visual query language
Author(s): John P. Oakley; Darryl N. Davis; Richard T. Shann
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Paper Abstract

We report a database language for visual retrieval which allows queries on image feature information which has been computed and stored along with images. The language is novel in that it provides facilities for dealing with feature data which has actually been obtained from image analysis. Each line in the Manchester Visual Query Language (MVQL) takes a set of objects as input and produces another, usually smaller, set as output. The MVQL constructs are mainly based on proven operators from the field of digital image analysis. An example is the Hough-group operator which takes as input a specification for the objects to be grouped, a specification for the relevant Hough space, and a definition of the voting rule. The output is a ranked list of high scoring bins. The query could be directed towards one particular image or an entire image database, in the latter case the bins in the output list would in general be associated with different images. We have implemented MVQL in two layers. The command interpreter is a Lisp program which maps each MVQL line to a sequence of commands which are used to control a specialized database engine. The latter is a hybrid graph/relational system which provides low-level support for inheritance and schema evolution. In the paper we outline the language and provide examples of useful queries. We also describe our solution to the engineering problems associated with the implementation of MVQL.

Paper Details

Date Published: 14 April 1993
PDF: 11 pages
Proc. SPIE 1908, Storage and Retrieval for Image and Video Databases, (14 April 1993); doi: 10.1117/12.143639
Show Author Affiliations
John P. Oakley, Manchester Univ. (United Kingdom)
Darryl N. Davis, Manchester Univ. (United Kingdom)
Richard T. Shann, Manchester Univ. (United Kingdom)


Published in SPIE Proceedings Vol. 1908:
Storage and Retrieval for Image and Video Databases
Carlton Wayne Niblack, Editor(s)

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