Content-Based Image Retrieval Using Shifted Histogram

Authors:
Gi-Hyoung Yoo;Beob Kyun Kim;Kang Soo You
Affiliations:
Department of Computer Engineering, Chonbuk National University, Jeonju, 561-756, Korea;Korea Institute of science and technology Information, Daejeon, 350-806, Korea;School of Liberal Arts, Jeonju University, Jeonju, 561-756, Korea
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
Year:
2007

Citing 3
Cited 2

Color indexing

International Journal of Computer Vision
Performance evaluation in content-based image retrieval: overview and proposals

Pattern Recognition Letters - Special issue on image/video indexing and retrieval
Query by Image and Video Content: The QBIC System

Computer

Directed enumeration method in image recognition

Pattern Recognition
Probabilistic neural network with homogeneity testing in recognition of discrete patterns set

Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes the shifted histogram method (SHM), for histogram-based image retrieval based on the dominant colors in images. The histogram-based method is very suitable for color image retrieval because retrievals are unaffected by geometrical changes in images, such as translation and rotation. Images with the same visual information, but with shifted color intensity, may significantly degrade if the conventional histogram intersection method (HIM) is used. In order to solve this problem, we propose the shifted histogram method (SHM). Our experimental results show that the shifted histogram method