Experiments of Distance Measurements in a Foliage Plant Retrieval System
Abstract
One of important components in an image retrieval system is selecting a distance measure to compute rank between two objects. In this paper, several distance measures were researched to implement a foliage plant retrieval system. Sixty kinds of foliage plants with various leaf color and shape were used to test the performance of 7 different kinds of distance measures: city block distance, Euclidean distance, Canberra distance, Bray-Curtis distance, x2 statistics, Jensen Shannon divergence and Kullback Leibler divergence. The results show that city block and Euclidean distance measures gave the best performance among the others.
Cite
@article{arxiv.1401.3584,
title = {Experiments of Distance Measurements in a Foliage Plant Retrieval System},
author = {Abdul Kadir and Lukito Edi Nugroho and Adhi Susanto and Paulus Insap Santosa},
journal= {arXiv preprint arXiv:1401.3584},
year = {2014}
}
Comments
14 pages, International Journal of Signal Processing, Image Processing and Pattern Recognition Vol. 5, No. 2, June, 2012