NDLI: Ontological shape-description, a new method for visual information retrieval

Content Provider	IEEE Xplore Digital Library
Author	Chavez-Aragon, A. Starostenko, O.
Copyright Year	2004
Description	Author affiliation: Comput. Sci. Dept., Univ. de las Americas Puebla, Mexico (Chavez-Aragon, A.; Starostenko, O.)
Abstract	There is a growing need for efficient visual information retrieval systems which take into account particular features of images, in order to avoid nonsensical results. We propose a new method for content-based image retrieval, which can be divided into two main parts: 1) automatic segmentation and extraction of shapes from image sub-regions; 2) ontological descriptions of shapes contained in the images. Our method allows users to perform sketch queries; these are simple drawings which represent the main idea of something the user is expecting to retrieve from the results. Once the user introduces a sketch, it is simplified using discrete curve evolution; then it is turned into a tangent space representation. Similarity measures based on turning functions are used to recover similar images. Ontology reduces the proportion of nonsensical results since it permits the recovery of images related semantically, even if they do not have similar shapes.
Sponsorship	Dept. of Elec. and Electron. Eng. of the Universidad de las Americas Puebla (UDLAP) Center for Res. in Information and Automation Technol. (CENTIA) - UDLAP Volkswagen of Mexico IEEE Section Puebla/Mexico FESTO Mexico
Starting Page	288
Ending Page	292
File Size	301601
Page Count	5
File Format	PDF
ISBN	076952074X
DOI	10.1109/ICECC.2004.1269588
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-02-16
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Ontologies Information retrieval Image retrieval Shape Content based retrieval Multimedia systems Image analysis Image color analysis SQUIDs Computer science
Content Type	Text
Resource Type	Article

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