Paper
1 April 1994 Bounds for the discrimination power of color indexing techniques
Markus Andreas Stricker
Author Affiliations +
Proceedings Volume 2185, Storage and Retrieval for Image and Video Databases II; (1994) https://doi.org/10.1117/12.171784
Event: IS&T/SPIE 1994 International Symposium on Electronic Imaging: Science and Technology, 1994, San Jose, CA, United States
Abstract
Most color indexing techniques proposed in the literature are similar: images are represented by color histograms, and a metric on the color histogram space is used to determine the similarity of images. In this paper we determine the limits of these color indexing techniques. We propose two functions to measure the discrimination power of indexing techniques: the capacity (how many distinguishable histograms can be stored) and the maximal match number (the maximal number of retrieved images). We derive bounds for these functions. These bounds have two practical aspects. First, they help a user to decide whether color histograms effectively index database images from a given domain. Second, they facilitate the choice of a good threshold for the distance below which histograms are considered similar. Our arguments are based on an analysis of the metrical properties of the histogram space and results from coding theory. The results show that over a large range of reasonable parameters the capacity is very large. Thus, the set of parameters for which color indexing works well can be described as the set of parameters for which the maximal match number is below an application-dependent maximum.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Markus Andreas Stricker "Bounds for the discrimination power of color indexing techniques", Proc. SPIE 2185, Storage and Retrieval for Image and Video Databases II, (1 April 1994); https://doi.org/10.1117/12.171784
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Cited by 27 scholarly publications.
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KEYWORDS
Databases

Image retrieval

Coding theory

Binary data

Distance measurement

Data modeling

Algorithm development

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