  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.
