Color, Texture, and Shape Features for Content-Based Image Retrieval
She, Alfred Chia-Hwa
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/81254
Description
Title
Color, Texture, and Shape Features for Content-Based Image Retrieval
Author(s)
She, Alfred Chia-Hwa
Issue Date
1998
Doctoral Committee Chair(s)
Huang, Thomas S.
Department of Study
Electrical Engineering
Discipline
Electrical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Electronics and Electrical
Language
eng
Abstract
The main contributions of our work are towards the development of a prototype content-based retrieval system, the Multimedia Analysis and Retrieval System (MARS), a joint effort by several research groups under the Digital Library Initiative. In MARS, we have developed and implemented a shape-matching method that is very fast computationally and invariant to rotation, translation, scale, and spatial quantization. We propose several generalizations of monochrome texture methods to work with color images and discuss their use in segmentation. We also perform a database retrieval accuracy test to quantitatively compare the performance of several texture methods. Based on the test results, we make observations on how color information can improve classification.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
