| Description |
This package provides implementations of several commonly used histogram
distances:
- Kullback-Leibler Divergence
- Jenson-Shannon Divergence
- Jeffrey Divergence
- Chi-Square
- Kolmogorov-Smirnov
- (Histogram) Intersection
- (Histogram) Match
- Quadratic form
The package comes with an example of color image matching (although this might
not be the best application idea, imho; anyway, it showcases the code).
I have applied some of the histogram distance functions for outlier reduction
when learning color term/name models from web images, see:
[1] B. Schauerte, G. A. Fink, "Web-based Learning of Naturalized Color Models
for Human-Machine Interaction". In Proceedings of the 12th International
Conference on Digital Image Computing: Techniques and Applications
(DICTA), IEEE, Sydney, Australia, December 1-3, 2010.
[2] B. Schauerte, R. Stiefelhagen, "Learning Robust Color Name Models from Web
Images". In Proceedings of the 21st International Conference on Pattern
Recognition (ICPR), Tsukuba, Japan, November 11-15, 2012
If you use and like this code, you are kindly requested to cite some of
the work above. |
