Color sets with morphological and B-spline enhancements for content-based image retrieval

Persistent Link:
http://hdl.handle.net/10150/280430
Title:
Color sets with morphological and B-spline enhancements for content-based image retrieval
Author:
Mlsna, Phillip Anthony
Issue Date:
2001
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Databases of color images have become increasingly important in recent years. The text-based retrieval of images in such databases is practical only if descriptive text annotations accompany each image. Creating such text descriptions is a labor intensive process requiring human interpretation of each image. Except for relatively small, static collections of images, the cost of generating text annotations is prohibitive. The desire to avoid the use of text-based image descriptors has therefore led to the investigation of feature-based descriptors that can automatically be extracted from images and indexed in the database. The definitions of these features and the algorithms for their automated extraction from a given image are the foci of most of the current research into Content-Based Image Retrieval (CBIR). This work focuses on improving the computational efficiency of the well-known color set algorithm for content-based image retrieval. The color set concept is a useful and efficient approach to image indexing and query in a way that combines color and spatial information. By indexing relatively important regions based on both their color content and their spatial locations, the color set method allows rapid retrieval of images matching a specified color-spatial query. Several refinements of the color set approach are presented in this dissertation. First, the process of determining the relevant color combinations for color sets to be indexed has been made approximately one to two orders of magnitude more efficient than the original algorithm. Second, a B-spline descriptor of region shape, size, and position has been incorporated to supplement the original method's rectangular bounding box. Describing contours as closed B-spline curves provides an accurate and storage-efficient means of indexing region location and shape. During image query, the convex hull property of B-spline curves is exploited to enable efficient determination of region containment of a specific point. Finally, an idea for improving the computational efficiency of approximating region contours with periodic, quadratic B-spline curves is briefly discussed.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Engineering, Electronics and Electrical.; Computer Science.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Electrical and Computer Engineering
Degree Grantor:
University of Arizona
Advisor:
Rodriguez, Jeffrey J.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleColor sets with morphological and B-spline enhancements for content-based image retrievalen_US
dc.creatorMlsna, Phillip Anthonyen_US
dc.contributor.authorMlsna, Phillip Anthonyen_US
dc.date.issued2001en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractDatabases of color images have become increasingly important in recent years. The text-based retrieval of images in such databases is practical only if descriptive text annotations accompany each image. Creating such text descriptions is a labor intensive process requiring human interpretation of each image. Except for relatively small, static collections of images, the cost of generating text annotations is prohibitive. The desire to avoid the use of text-based image descriptors has therefore led to the investigation of feature-based descriptors that can automatically be extracted from images and indexed in the database. The definitions of these features and the algorithms for their automated extraction from a given image are the foci of most of the current research into Content-Based Image Retrieval (CBIR). This work focuses on improving the computational efficiency of the well-known color set algorithm for content-based image retrieval. The color set concept is a useful and efficient approach to image indexing and query in a way that combines color and spatial information. By indexing relatively important regions based on both their color content and their spatial locations, the color set method allows rapid retrieval of images matching a specified color-spatial query. Several refinements of the color set approach are presented in this dissertation. First, the process of determining the relevant color combinations for color sets to be indexed has been made approximately one to two orders of magnitude more efficient than the original algorithm. Second, a B-spline descriptor of region shape, size, and position has been incorporated to supplement the original method's rectangular bounding box. Describing contours as closed B-spline curves provides an accurate and storage-efficient means of indexing region location and shape. During image query, the convex hull property of B-spline curves is exploited to enable efficient determination of region containment of a specific point. Finally, an idea for improving the computational efficiency of approximating region contours with periodic, quadratic B-spline curves is briefly discussed.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectEngineering, Electronics and Electrical.en_US
dc.subjectComputer Science.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineElectrical and Computer Engineeringen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorRodriguez, Jeffrey J.en_US
dc.identifier.proquest3010248en_US
dc.identifier.bibrecord.b41711270en_US
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