DocumentCode :
677251
Title :
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
Link To Document :
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