International Journal of Computer Vision
Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
A web-based evaluation system for CBIR
MULTIMEDIA '01 Proceedings of the 2001 ACM workshops on Multimedia: multimedia information retrieval
Image Indexing Using Color Correlograms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A Weighted Distance Approach to Relevance Feedback
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Robust Histogram Construction from Color Invariants for Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Similarity between Euclidean and cosine angle distance for nearest neighbor queries
Proceedings of the 2004 ACM symposium on Applied computing
The analysis and applications of adaptive-binning color histograms
Computer Vision and Image Understanding - Special issue on color for image indexing and retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Soccer video processing for the detection of advertisement billboards
Pattern Recognition Letters
An Efficient Particle Filter---based Tracking Method Using Graphics Processing Unit (GPU)
Journal of Signal Processing Systems
Object recognition using Gabor co-occurrence similarity
Pattern Recognition
An Expert Support System for Breast Cancer Diagnosis using Color Wavelet Features
Journal of Medical Systems
Modified color motif co-occurrence matrix for image indexing and retrieval
Computers and Electrical Engineering
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The paper presents a novel approach for representing color and intensity of pixel neighborhoods in an image using a co-occurrence matrix. After analyzing the properties of the HSV color space, suitable weight functions have been suggested for estimating relative contribution of color and gray levels of an image pixel. The suggested weight values for a pixel and its neighbor are used to construct an Integrated Color and Intensity Co-occurrence Matrix (ICICM). We have shown that if the ICICM matrix is used as a feature in an image retrieval application, it is possible to have higher recall and precision compared to other existing methods.