Butterfly Species Recognition Using Artificial Neural Network (ANN)

In 2017, there are about 20,000 species of butterfly has been discovered all over the world. Butterfly is well known because of its beautiful wings pattern and its benefits to the environment. In this research, butterfly species recognition is automated using artificial intelligence. Pattern on the...

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Main Author: Yong, Kai Xin
Format: Monograph
Language:English
Published: Universiti Sains Malaysia 2017
Subjects:
Online Access:http://eprints.usm.my/52927/1/Butterfly%20Species%20Recognition%20Using%20Artificial%20Neural%20Network%20%28ANN%29_Yong%20Kai%20Xin_E3_2017.pdf
http://eprints.usm.my/52927/
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spelling my.usm.eprints.52927 http://eprints.usm.my/52927/ Butterfly Species Recognition Using Artificial Neural Network (ANN) Yong, Kai Xin T Technology In 2017, there are about 20,000 species of butterfly has been discovered all over the world. Butterfly is well known because of its beautiful wings pattern and its benefits to the environment. In this research, butterfly species recognition is automated using artificial intelligence. Pattern on the butterfly wings is used as a parameter to determine the species of the butterfly. The butterfly image is captured and the background of the image is removed to make the recognition process easier. Local binary pattern (LBP) descriptor is then applied to the processed image and a histogram consist of image information is computed. Artificial neural network (ANN) is used to classify the image. Universiti Sains Malaysia 2017-06-01 Monograph NonPeerReviewed application/pdf en http://eprints.usm.my/52927/1/Butterfly%20Species%20Recognition%20Using%20Artificial%20Neural%20Network%20%28ANN%29_Yong%20Kai%20Xin_E3_2017.pdf Yong, Kai Xin (2017) Butterfly Species Recognition Using Artificial Neural Network (ANN). Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Elektrik & Elektronik. (Submitted)
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic T Technology
spellingShingle T Technology
Yong, Kai Xin
Butterfly Species Recognition Using Artificial Neural Network (ANN)
description In 2017, there are about 20,000 species of butterfly has been discovered all over the world. Butterfly is well known because of its beautiful wings pattern and its benefits to the environment. In this research, butterfly species recognition is automated using artificial intelligence. Pattern on the butterfly wings is used as a parameter to determine the species of the butterfly. The butterfly image is captured and the background of the image is removed to make the recognition process easier. Local binary pattern (LBP) descriptor is then applied to the processed image and a histogram consist of image information is computed. Artificial neural network (ANN) is used to classify the image.
format Monograph
author Yong, Kai Xin
author_facet Yong, Kai Xin
author_sort Yong, Kai Xin
title Butterfly Species Recognition Using Artificial Neural Network (ANN)
title_short Butterfly Species Recognition Using Artificial Neural Network (ANN)
title_full Butterfly Species Recognition Using Artificial Neural Network (ANN)
title_fullStr Butterfly Species Recognition Using Artificial Neural Network (ANN)
title_full_unstemmed Butterfly Species Recognition Using Artificial Neural Network (ANN)
title_sort butterfly species recognition using artificial neural network (ann)
publisher Universiti Sains Malaysia
publishDate 2017
url http://eprints.usm.my/52927/1/Butterfly%20Species%20Recognition%20Using%20Artificial%20Neural%20Network%20%28ANN%29_Yong%20Kai%20Xin_E3_2017.pdf
http://eprints.usm.my/52927/
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score 13.18916