Evaluation of distance measures for partial image retrieval using self-organizing map

1Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Digital image libraries are becoming more common and widely used as more visual information is produced at a rapidly growing rate. With this immense growth, there is a need to organize and index these databases so that we can efficiently retrieve the desired images. In this paper, we evaluate the performance of the self-organising maps (SOMs) with different distance measures in retrieving similar images when a full or a partial query image is presented to the SOM. Our method makes use of RGB colour histograms. As the RGB colour space is very large, another SOM is employed to adaptively quantise the colour space prior to generating the histograms. Some promising results are reported.

Cite

CITATION STYLE

APA

Huang, Y., Suganthan, P. N., Krishnan, S. M., & Cao, X. (2001). Evaluation of distance measures for partial image retrieval using self-organizing map. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2130, pp. 1042–1047). Springer Verlag. https://doi.org/10.1007/3-540-44668-0_144

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free