Image indexing using color correlograms

We define a new image feature called the color correlogram and use it for image indexing and comparison. This feature distills the spatial correlation of colors, and is both effective and inexpensive for content-based image retrieval. The correlogram robustly tolerates large changes in appearance and shape caused by changes in viewing positions, camera zooms, etc. Experimental evidence suggests that this new feature outperforms not only the traditional color histogram method but also the recently proposed histogram refinement methods for image indexing/retrieval.

[1]  G. J. G. Upton,et al.  Spatial data Analysis by Example , 1985 .

[2]  Peter J. Rousseeuw,et al.  Robust regression and outlier detection , 1987 .

[3]  T. Coburn.  Spatial Data Analysis by Example , 1991 .

[4]  David Haussler,et al.  Decision Theoretic Generalizations of the PAC Model for Neural Net and Other Learning Applications , 1992, Inf. Comput..

[5]  Harpreet Sawhney,et al.  Efficient color histogram indexing , 1994, Proceedings of 1st International Conference on Image Processing.

[6]  Vijay V. Raghavan,et al.  Content-Based Image Retrieval Systems - Guest Editors' Introduction , 1995, Computer.

[7]  Michael Stonebraker,et al.  Chabot: Retrieval from a Relational Database of Images , 1995, Computer.

[8]  Dragutin Petkovic,et al.  Query by Image and Video Content: The QBIC System , 1995, Computer.

[9]  James Lee Hafner,et al.  Efficient Color Histogram Indexing for Quadratic Form Distance Functions , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Shih-Fu Chang,et al.  Tools and techniques for color image retrieval , 1996, Electronic Imaging.

[11]  Markus A. Stricker,et al.  Color indexing with weak spatial constraints , 1996, Electronic Imaging.

[12]  T. John Stonham,et al.  Content-based image retrieval using color tuple histograms , 1996, Electronic Imaging.

[13]  Ramin Zabih,et al.  Histogram refinement for content-based image retrieval , 1996, Proceedings Third IEEE Workshop on Applications of Computer Vision. WACV'96.

[14]  Ingemar J. Cox,et al.  PicHunter: Bayesian relevance feedback for image retrieval , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[15]  M.,et al.  Statistical and Structural Approaches to Texture , 2022 .