Experiments of Distance Measurements in a Foliage Plant Retrieval System

11/20/2013
by   Abdul Kadir, et al.
0

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.

READ FULL TEXT

page 6

page 9

page 14

research
11/24/2016

Comparative study of histogram distance measures for re-identification

Color based re-identification methods usually rely on a distance functio...
research
08/05/2018

Prediction in Riemannian metrics derived from divergence functions

Divergence functions are interesting discrepancy measures. Even though t...
research
10/02/2012

A fast compression-based similarity measure with applications to content-based image retrieval

Compression-based similarity measures are effectively employed in applic...
research
06/03/2015

Color Image Retrieval Using Fuzzy Measure Hamming and S-Tree

This chapter approaches the image retrieval system on the base of the co...
research
03/20/2019

Note on bounds for symmetric divergence measures

I. Sason obtained the tight bounds for symmetric divergence measures are...
research
05/03/2023

Quantifying the Dissimilarity of Texts

Quantifying the dissimilarity of two texts is an important aspect of a n...
research
09/02/2019

Performance comparison of 3D correspondence grouping algorithm for 3D plant point clouds

Plant Phenomics can be used to monitor the health and the growth of plan...

Please sign up or login with your details

Forgot password? Click here to reset