International Journal of Computer Vision
Comparing images using color coherence vectors
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Communications of the ACM
Comparing images using joint histograms
Multimedia Systems - Special issue on video content based retrieval
A relevance feedback mechanism for content-based image retrieval
Information Processing and Management: an International Journal
ImageRover: A Content-Based Image Browser for the World Wide Web
CAIVL '97 Proceedings of the 1997 Workshop on Content-Based Access of Image and Video Libraries (CBAIVL '97)
Image Indexing Using Color Correlograms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Histogram refinement for content-based image retrieval
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
Learning to rank for content-based image retrieval
Proceedings of the international conference on Multimedia information retrieval
Approximate image color correlograms
Proceedings of the international conference on Multimedia
A compact auto color correlation using binary coding stream for image retrieval
Proceedings of the 15th WSEAS international conference on Computers
Comparative study of global color and texture descriptors for web image retrieval
Journal of Visual Communication and Image Representation
Computer Vision and Image Understanding
Sinimbu --- multimodal queries to support biodiversity studies
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part I
Using contextual spaces for image re-ranking and rank aggregation
Multimedia Tools and Applications
Multimodal retrieval with relevance feedback based on genetic programming
Multimedia Tools and Applications
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The comparison of digital images to determine their degree of similarity is one of the fundamental problems of computer vision. Many techniques exist which accomplish this with a certain level of success, most of which involve either the analysis of pixel-level features or the segmentation of images into sub-objects that can be geometrically compared. In this paper we develop and evaluate a new variation of the pixel feature and analysis technique known as the color correlogram in the context of a content-based image retrieval system. Our approach is to extend the autocorrelogram by adding multiple image features in addition to color. We compare the performance of each index scheme with our method for image retrieval on a large database of images. The experiment shows that our proposed method gives a significant improvement over histogram or color correlogram indexing, and it is also memory-efficient.