Object-based image retrieval using dominant color pairs between adjacent regions

Authors:
Ki Tae Park;Young Shik Moon
Affiliations:
Dept. of Computer Science and Engineering, Hanyang University, Ansan, Korea;Dept. of Computer Science and Engineering, Hanyang University, Ansan, Korea
Venue:
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part V
Year:
2006

Citing 9
Cited 0

Color indexing

International Journal of Computer Vision
VisualSEEk: a fully automated content-based image query system

MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
A novel vector-based approach to color image retrieval using a vector angular-based distance measure

Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
FOCUS: Searching for Multi-colored Objects in a Diverse Image Database

CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Image Indexing Using Color Correlograms

CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
NeTra: a toolbox for navigating large image databases

ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
Spatial color descriptor for image retrieval and video segmentation

IEEE Transactions on Multimedia
Unsupervised video segmentation based on watersheds and temporal tracking

IEEE Transactions on Circuits and Systems for Video Technology
Color and texture descriptors

IEEE Transactions on Circuits and Systems for Video Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

Most existing methods for content-based image retrieval handle an image as a whole, instead of focusing on an object of interest. This paper proposes object-based image retrieval based on the dominant color pairs between adjacent regions. From a segmented image, the dominant color pairs between adjacent regions are extracted to produce color adjacency matrix, from which candidate regions of DB images are selected. The similarity measure between the query image and candidate regions in DB images is computed based on the color correlogram technique. Experimental results show the performance improvement of the proposed method over existing methods.