A new content-based image retrieval technique using color and texture information

Authors:
Xiang-Yang Wang;Hong-Ying Yang;Dong-Ming Li
Affiliations:
School of Computer and Information Technology, Liaoning Normal University, Dalian 116029, China;School of Computer and Information Technology, Liaoning Normal University, Dalian 116029, China;School of Computer and Information Technology, Liaoning Normal University, Dalian 116029, China
Venue:
Computers and Electrical Engineering
Year:
2013

Citing 25
Cited 0

An Evaluation of Color-Spatial Retrieval Techniques for Large Image Databases

Multimedia Tools and Applications
Performance evaluation and optimization for content-based image retrieval

Pattern Recognition
Color image retrieval technique based on color features and image bitmap

Information Processing and Management: an International Journal - Special issue: AIRS2005: Information retrieval research in Asia
Texture image retrieval using rotated wavelet filters

Pattern Recognition Letters
Rotation-invariant and scale-invariant Gabor features for texture image retrieval

Image and Vision Computing
Integrated color, texture and shape information for content-based image retrieval

Pattern Analysis & Applications
A fast MPEG-7 dominant color extraction with new similarity measure for image retrieval

Journal of Visual Communication and Image Representation
Content Based Image Retrieval Using Color, Texture and Shape Features

ADCOM '07 Proceedings of the 15th International Conference on Advanced Computing and Communications
Image retrieval: Ideas, influences, and trends of the new age

ACM Computing Surveys (CSUR)
Features for image retrieval: an experimental comparison

Information Retrieval
Image Retrieval Using Maximum Frequency of Local Histogram Based Color Correlogram

AMS '08 Proceedings of the 2008 Second Asia International Conference on Modelling & Simulation (AMS)
Effective image retrieval using dominant color descriptor and fuzzy support vector machine

Pattern Recognition
Color Descriptors for Web Image Retrieval: A Comparative Study

SIBGRAPI '08 Proceedings of the 2008 XXI Brazilian Symposium on Computer Graphics and Image Processing
Perplexity-based evidential neural network classifier fusion using mpeg-7 low-level visual features

MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Texture image retrieval based on non-tensor product wavelet filter banks

Signal Processing
A histogram-based approach for object-based query-by-shape-and-color in image and video databases

Image and Vision Computing
Morphological description of color images for content-based image retrieval

IEEE Transactions on Image Processing
An effective image retrieval scheme using color, texture and shape features

Computer Standards & Interfaces
Image Retrieval System Based on Adaptive Color Histogram and Texture Features

The Computer Journal
Plant Image Retrieval Using Color, Shape and Texture Features

The Computer Journal
Color and texture image retrieval using chromaticity histograms and wavelet frames

IEEE Transactions on Multimedia
Content-Based Image Retrieval Using Multiresolution Color and Texture Features

IEEE Transactions on Multimedia
The contourlet transform: an efficient directional multiresolution image representation

IEEE Transactions on Image Processing
Rotation-Invariant Texture Retrieval via Signature Alignment Based on Steerable Sub-Gaussian Modeling

IEEE Transactions on Image Processing
Image retrieval using BDIP and BVLC moments

IEEE Transactions on Circuits and Systems for Video Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

Feature extraction and representation is one of the most important issues in the content-based image retrieval. In this paper, we propose a new content-based image retrieval technique using color and texture information, which achieves higher retrieval efficiency. Firstly, the image is transformed from RGB space to opponent chromaticity space, and the characteristics of the color contents of an image is captured by using Zernike chromaticity distribution moments from the chromaticity space. Secondly, the texture features are extracted using a rotation-invariant and scale-invariant image descriptor in Contourlet domain, which offers an efficient and flexible approximation of early processing in the human visual system. Finally, the combination of the color and texture information provides a robust feature set for color image retrieval. Experimental results show that the proposed color image retrieval is more accurate and efficient in retrieving the user-interested images.