Region filtering using color and texture features for image retrieval

Authors:
Cheng-Chieh Chiang;Ming-Han Hsieh;Yi-Ping Hung;Greg C. Lee
Affiliations:
Department of Information and Computer Education, National Taiwan Normal University, Taipei, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan, R.O.C.;Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan, R.O.C.;Department of Information and Computer Education, National Taiwan Normal University, Taipei, Taiwan, R.O.C.
Venue:
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
Year:
2005

Citing 8
Cited 1

Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations

IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Features for Browsing and Retrieval of Image Data

IEEE Transactions on Pattern Analysis and Machine Intelligence
The Earth Mover's Distance as a Metric for Image Retrieval

International Journal of Computer Vision
SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries

IEEE Transactions on Pattern Analysis and Machine Intelligence
Blobworld: A System for Region-Based Image Indexing and Retrieval

VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
Automatic image annotation and retrieval using cross-media relevance models

Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Efficient region-based image retrieval

CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
An efficient and effective region-based image retrieval framework

IEEE Transactions on Image Processing

Region-based image retrieval using color-size features of watershed regions

Journal of Visual Communication and Image Representation

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a region-based image retrieval (RBIR) system in which users can choose specific regions as the query. Our goal is to assist the user to formulate more precise queries with which the retrieval system can focus on the user’s interested part. In this work, images are partitioned into a set of regions by using the watershed segmentation. Color-size histogram and Gabor texture features are extracted from each watershed region. We propose a scheme of region filtering based on individual features, rather than integrating different features, to reduce the computational load of the image retrieval. This paper also defines the dissimilarity measure of images, and therefore relevance feedback is used for improving our retrieval. Finally we describe some experimental results of our RBIR system.