Please use this identifier to cite or link to this item:
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/73881
Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Nur Anis Nabila, Mohamad Marzuki | - |
dc.contributor | School of Bioprocess Engineering | en_US |
dc.date | 2021 | - |
dc.date.accessioned | 2022-01-28T01:46:42Z | - |
dc.date.available | 2022-01-28T01:46:42Z | - |
dc.date.issued | 2017-05 | - |
dc.identifier.uri | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/73881 | - |
dc.description | Access is limited to UniMAP community. | en_US |
dc.description.abstract | Banana is one of the most important food sources which contains lot of vitamins and carbohydrate that is important to be consumed in daily diet. Bananas are well known in the world trade as it has higher market value. Most of the suppliers and fruit sellers sorted out banana manually according to their visual inspection which takes into account the external peel color changes as the parameter to determine its quality. The whole process is time consuming, required higher cost; labor intensive and makes it as a slow process. The purpose of this study is to detect the development of brown spot of banana at different ripening stages (RS) by using computer vision system. In this study, 40 banana samples were used in image acquisition. The image was captured by using Charged Coupled Device (CCD) camera set up in a black box. All the banana images were undergo image processing which are pre-processing to permit pre-smoothing of noisy images, enhance the contrast and improve their quality. The image processing procedures such as IMAQ Threshold were carried out in the LabVIEW programming software. The percentage of brown spot area data were extracted based on the acquired image. All of the extracted data were analyzed using Analysis of Variance (ANOVA). From the analysis, the developed RS of banana are used for better knowledge to determine the banana maturity stages. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Universiti Malaysia Perlis (UniMAP) | en_US |
dc.subject.other | Banana | en_US |
dc.subject.other | Ripening stages (RS) | en_US |
dc.subject.other | Computer vision system | en_US |
dc.subject.other | Brown spot | en_US |
dc.title | Development of vision system for detection of brown spot on banana at different ripening stages | en_US |
dc.type | Learning Object | en_US |
dc.contributor.advisor | Aimi Athirah, Aznan | - |
Appears in Collections: | School of Bioprocess Engineering (FYP) |
Files in This Item:
File | Description | Size | Format | |
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Abstract, Acknowledgement.pdf | 430.88 kB | Adobe PDF | View/Open | |
Introduction.pdf | 222.1 kB | Adobe PDF | View/Open | |
Literature Review.pdf | 405.96 kB | Adobe PDF | View/Open | |
Methodology.pdf | 672.75 kB | Adobe PDF | View/Open | |
Result and Discussion.pdf | 354.86 kB | Adobe PDF | View/Open | |
Conclusion and Recommendations.pdf | 108.77 kB | Adobe PDF | View/Open | |
References and Appendices.pdf | 408.29 kB | Adobe PDF | View/Open |
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