The Role Of Massive Color Quantization In Object Recognition

Author

S. Redfield
J. G. Harris, Missouri University of Science and TechnologyFollow

Abstract

Psychophysical experimental inspire a more complete analysis of the effect of quantization on a modified version of the histogram indexing method of object recognition. We derive an equation that describes how the amount of quantization and number of features kept affects recognition accuracy. The equation shows that quantization from 2²⁴ colors to 15 colors has a negligible effect on accuracy. A simulation shows that large numbers of objects cause a corresponding decrease in accuracy, but that keeping more features can increase the accuracy even for massive quantization. An object recognition experiment with real data shows dramatically better results when quantization is used, indicating that massive color quantization can provide some invariance to lighting conditions.

Recommended Citation

S. Redfield and J. G. Harris, "The Role Of Massive Color Quantization In Object Recognition," IEEE International Conference on Image Processing, vol. 1, pp. 57 - 60, Institute of Electrical and Electronics Engineers, Dec 2000.

Department(s)

Electrical and Computer Engineering

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2025 Institute of Electrical and Electronics Engineers, All rights reserved.

Publication Date

01 Dec 2000