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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| Format: | Monograph |
| Language: | English |
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Universiti Sains Malaysia
2017
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| Online Access: | http://eprints.usm.my/52927/ http://eprints.usm.my/52927/1/Butterfly%20Species%20Recognition%20Using%20Artificial%20Neural%20Network%20%28ANN%29_Yong%20Kai%20Xin_E3_2017.pdf |
| _version_ | 1848882384000253952 |
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| author | Yong, Kai Xin |
| author_facet | Yong, Kai Xin |
| author_sort | Yong, Kai Xin |
| building | USM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T18:34:03Z |
| format | Monograph |
| id | usm-52927 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T18:34:03Z |
| publishDate | 2017 |
| publisher | Universiti Sains Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-529272022-06-17T01:31:31Z 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) |
| spellingShingle | T Technology Yong, Kai Xin Butterfly Species Recognition Using Artificial Neural Network (ANN) |
| title | 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_short | Butterfly Species Recognition Using Artificial Neural Network (ANN) |
| title_sort | butterfly species recognition using artificial neural network (ann) |
| topic | T Technology |
| url | http://eprints.usm.my/52927/ http://eprints.usm.my/52927/1/Butterfly%20Species%20Recognition%20Using%20Artificial%20Neural%20Network%20%28ANN%29_Yong%20Kai%20Xin_E3_2017.pdf |