Classification of orchid species using Neural Network

Author

Sani, Maizura Mohd ; Kutty, Suhaili Beeran ; Omar, Hassan ; Md Isa, Ili Nadia

Author_Institution

Fac. of Electr. Eng., Univ. Teknol. Mara, Shah Alam, Malaysia

fYear

2013

fDate

Nov. 29 2013-Dec. 1 2013

Firstpage

586

Lastpage

589

Abstract

Orchid species have a largest families among the botanical plant. Basically, a species of orchid are visually recognizing from its color, root, petal shape or even the size. However, there are several orchid species that really look alike and the type could be falsely classified. The aim of this paper is to classify two species of orchids which are physically look identical, i.e. Dendrobium Madame Pampadour and Dendrobium Cqompactum using image processing techniques. Using Neural Network, the classification rate is 85.7%.

Keywords

botany; image recognition; neural nets; Dendrobium Cqompactum; Dendrobium Madame Pampadour; botanical plant; classification rate; color recognition; image processing techniques; neural network; orchid species classification; petal shape recognition; root recognition; size recognition; Accuracy; Biological neural networks; Conferences; Image color analysis; Testing; Training; Dendrobium Compactum; Dendrobium Madame Pampadour; Neural Network; Orchid Classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Control System, Computing and Engineering (ICCSCE), 2013 IEEE International Conference on

Conference_Location

Mindeb

Print_ISBN

978-1-4799-1506-4

Type

conf

DOI

10.1109/ICCSCE.2013.6720033

Filename

6720033