Paper Info
Title
Automatic identification of butterfly species based on local binary patterns and artificial neural network
Abstract
computer vision method was proposed for automatically identifying butterfly species.To our knowledge, it was the first study in identifying the butterfly species with computer vision.The method is based on local binary patterns and artificial neural network.Results demonstrated that the proposed method has achieved well recognition accuracy rates. Butterflies are classified firstly according to their outer morphological qualities. It is required to analyze genital characters of them when classification according to outer morphological qualities is not possible. Genital characteristics of a butterfly can be determined by using various chemical substances and methods. Currently, these processes are carried out manually by preparing genital slides of the collected butterfly through some certain processes. For some groups of butterflies molecular techniques should be applied for identification which is expensive to use. In this study, a computer vision method is proposed for automatically identifying butterfly species as an alternative to conventional identification methods. The method is based on local binary pattern (LBP) and artificial neural network (ANN). A total of 50 butterfly images of five species were used for evaluating the effectiveness of the proposed method. Experimental results demonstrated that the proposed method has achieved well recognition in terms of accuracy rates for butterfly species identification.
Year
DOI
Venue
2015
10.1016/j.asoc.2014.11.046
Applied Soft Computing
Keywords
Field
DocType
local binary patterns,artificial neural network
Local binary patterns,Species identification,Artificial intelligence,Butterfly,Artificial neural network,Machine learning,Mathematics
Journal
Volume
Issue
ISSN
28
C
1568-4946
Citations 
PageRank 
References 
6
0.68
18
Authors
3
Name
Order
Citations
PageRank
Yilmaz Kaya114412.98
Lokman Kayci2362.48
Murat Uyar31126.98