JOURNAL ARTICLE

<title>Content-based image retrieval using multiresolution histogram representation</title>

Asha VellaikalC.‐C. Jay Kuo

Year: 1995 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 2606 Pages: 312-323   Publisher: SPIE

Abstract

We present two new approaches based on color histogram indexing for content-based retrieval of image databases. Since the high computational complexity has been one of the main barriers towards the use of similarity measures such as histogram intersection in large databases, we propose a hierarchical indexing scheme where computationally efficient features are used to subset the image before more sophisticated techniques are applied for precise retrieval. The use of histograms at different color resolutions as filtering and matching features in a hierarchical scheme is studied. In the second approach, a multiresolution representation of the histogram using the indices and signs of its largest wavelet coefficients is examined. Excellent results have been observed using the latter method.

Keywords:
Histogram Histogram matching Search engine indexing Computer science Pattern recognition (psychology) Artificial intelligence Image retrieval Representation (politics) Content-based image retrieval Similarity (geometry) Color histogram Matching (statistics) Image (mathematics) Computer vision Mathematics Image processing Color image Statistics

Metrics

22
Cited By
0.94
FWCI (Field Weighted Citation Impact)
0
Refs
0.76
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Neural Networks and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence

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