Multi sensor system for classifying harumanis mango based on external and internal quality/
The main objective of this thesis is to develop a system using machine vision and NIR spectrometer for classifying Harumanis mango based on its shape, mass and TSS. The objectives of this research are divided and addressed as below; to develop 3-Dimensional image acquisition technique for capturing...
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| Format: | Thesis Software eBook |
| Language: | English |
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Perlis, Malaysia
School of Mechatronic Engineering, Universiti Malaysia Perlis
2017
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| 100 | 0 | |a Mohd Firdaus Ibrahim, |e author | |
| 245 | 1 | 0 | |a Multi sensor system for classifying harumanis mango based on external and internal quality/ |c Mohd Firdaus Bin Ibrahim |
| 264 | 1 | |a Perlis, Malaysia |b School of Mechatronic Engineering, Universiti Malaysia Perlis |c 2017 | |
| 300 | |a 1 CD-ROM |c 12 cm | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 502 | |a Thesis (Master of Science) -- Universiti Malaysia Perlis. School of Mechatronic Engineering, 2017 | ||
| 504 | |a Includes bibliographical references. | ||
| 520 | |a The main objective of this thesis is to develop a system using machine vision and NIR spectrometer for classifying Harumanis mango based on its shape, mass and TSS. The objectives of this research are divided and addressed as below; to develop 3-Dimensional image acquisition technique for capturing image of the mango on a moving conveyor; to analyse the Harumanis mango features and classify the mango based on the shape and mass; to analyse the total soluble solid (TSS) of the mango using Near Infrared (NIR) spectrometer. | ||
| 541 | |a Gift from Centre for Graduate Studies (Master of Science ) |b 2018 | ||
| 650 | 0 | |9 39 |a Image processing |x Digital techniques | |
| 650 | 0 | |9 41 |a Computer vision | |
| 650 | 1 | |9 40 |a Mango | |
| 710 | 2 | |a Universiti Malaysia Perlis | |
| 720 | 1 | |a Dr. Ammar Zakaria, |e supervisor | |
| 790 | 1 | |a School of Mechatronic Engineering | |
| 791 | 1 | |a Master of Science | |
| 792 | 1 | |a 2017 | |
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