Brovey Transform Based Image Fusion For Impurities Segmentation And Detection On Edible Bird’s Nest
Edible bird’s nest (EBN) is one of the most important products in food and agricultural industry in South East Asia. In Malaysia, the production of EBN soaring because of the exportation of EBN to meet the demand of overseas market. Assurance of cleanliness is one of the major difficulties fac...
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| Format: | Monograph |
| Language: | English |
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Universiti Sains Malaysia
2019
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| Online Access: | http://eprints.usm.my/58276/ http://eprints.usm.my/58276/1/Brovey%20Transform%20Based%20Image%20Fusion%20For%20Impurities%20Segmentation%20And%20Detection%20On%20Edible%20Bird%E2%80%99s%20Nest.pdf |
| _version_ | 1848883855609561088 |
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| author | Kee, Seow Pei |
| author_facet | Kee, Seow Pei |
| author_sort | Kee, Seow Pei |
| building | USM Institutional Repository |
| collection | Online Access |
| description | Edible bird’s nest (EBN) is one of the most important products in food and agricultural
industry in South East Asia. In Malaysia, the production of EBN soaring because of the
exportation of EBN to meet the demand of overseas market. Assurance of cleanliness
is one of the major difficulties faced in processing the EBN. Current cleaning method
of EBN is labour dependency, time consuming and not cost effective. Automated
inspection was introduced but still continues to exist as a challenging field of
development as there is no effective algorithms for impurities segmentation. Some
impurities have similar colour as EBN features which increase the complexity of image
processing. In this study, Brovey transform based image fusion is used to highlight the
impurities in EBN and ease the segmentation process. Various types of Multispectral
(MS) reference images were considered in image fusion process. Comparison was made
to obtain the MS reference image with highest accuracy of segmented region. The
performances of fused images are evaluated based on segmentation rate, precision,
accuracy, error rate and dice similarity index (DSI). The optimal performances were
achieved by the green light without erosion MS reference image with an overall
segmentation rate of 49.96%, precision of 48.78%, accuracy of 40.00%, error rate of
60% and DSI of 0.571. |
| first_indexed | 2025-11-15T18:57:27Z |
| format | Monograph |
| id | usm-58276 |
| institution | Universiti Sains Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T18:57:27Z |
| publishDate | 2019 |
| publisher | Universiti Sains Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | usm-582762023-04-28T09:11:12Z http://eprints.usm.my/58276/ Brovey Transform Based Image Fusion For Impurities Segmentation And Detection On Edible Bird’s Nest Kee, Seow Pei T Technology T Technology (General) Edible bird’s nest (EBN) is one of the most important products in food and agricultural industry in South East Asia. In Malaysia, the production of EBN soaring because of the exportation of EBN to meet the demand of overseas market. Assurance of cleanliness is one of the major difficulties faced in processing the EBN. Current cleaning method of EBN is labour dependency, time consuming and not cost effective. Automated inspection was introduced but still continues to exist as a challenging field of development as there is no effective algorithms for impurities segmentation. Some impurities have similar colour as EBN features which increase the complexity of image processing. In this study, Brovey transform based image fusion is used to highlight the impurities in EBN and ease the segmentation process. Various types of Multispectral (MS) reference images were considered in image fusion process. Comparison was made to obtain the MS reference image with highest accuracy of segmented region. The performances of fused images are evaluated based on segmentation rate, precision, accuracy, error rate and dice similarity index (DSI). The optimal performances were achieved by the green light without erosion MS reference image with an overall segmentation rate of 49.96%, precision of 48.78%, accuracy of 40.00%, error rate of 60% and DSI of 0.571. Universiti Sains Malaysia 2019-06-01 Monograph NonPeerReviewed application/pdf en http://eprints.usm.my/58276/1/Brovey%20Transform%20Based%20Image%20Fusion%20For%20Impurities%20Segmentation%20And%20Detection%20On%20Edible%20Bird%E2%80%99s%20Nest.pdf Kee, Seow Pei (2019) Brovey Transform Based Image Fusion For Impurities Segmentation And Detection On Edible Bird’s Nest. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Mekanik. (Submitted) |
| spellingShingle | T Technology T Technology (General) Kee, Seow Pei Brovey Transform Based Image Fusion For Impurities Segmentation And Detection On Edible Bird’s Nest |
| title | Brovey Transform Based Image Fusion For Impurities Segmentation And Detection On Edible Bird’s Nest |
| title_full | Brovey Transform Based Image Fusion For Impurities Segmentation And Detection On Edible Bird’s Nest |
| title_fullStr | Brovey Transform Based Image Fusion For Impurities Segmentation And Detection On Edible Bird’s Nest |
| title_full_unstemmed | Brovey Transform Based Image Fusion For Impurities Segmentation And Detection On Edible Bird’s Nest |
| title_short | Brovey Transform Based Image Fusion For Impurities Segmentation And Detection On Edible Bird’s Nest |
| title_sort | brovey transform based image fusion for impurities segmentation and detection on edible bird’s nest |
| topic | T Technology T Technology (General) |
| url | http://eprints.usm.my/58276/ http://eprints.usm.my/58276/1/Brovey%20Transform%20Based%20Image%20Fusion%20For%20Impurities%20Segmentation%20And%20Detection%20On%20Edible%20Bird%E2%80%99s%20Nest.pdf |