Color, Texture, and Shape Features for Content-Based Image Retrieval

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.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Electrical Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• She, Alfred Chia-Hwa

Contributors dc:contributor

• Huang, Thomas S.

• Engineering, Electronics and Electrical

Language dc:language

eng

Identifier

(MiAaPQ)AAI9904584

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/81254