Harumanis mango quality assessments technique based on high level features fusion of infra-red thermal and optical image
Doctor of Philosophy in Mechatronic Engineering
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Universiti Malaysia Perlis (UniMAP)
2017
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Online Access: | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72933 |
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my.unimap-729332021-12-17T02:44:30Z Harumanis mango quality assessments technique based on high level features fusion of infra-red thermal and optical image Fathinul Syahir, Ahmad Sa'ad Ali Yeon, Md. Shakaff, Prof. Dr. Harumanis mango Optical communication Harumanis Harumanis -- Quality inspection Machine Vision Doctor of Philosophy in Mechatronic Engineering Mangoes imported from other parts of the world, especially Malaysia, Thailand, Mexico and the Philippines, are usually available all year round but in Perlis, Malaysia there is one unique and famous mango is Harumanis mango and this fruit is seasonal. Every year, a large amount of mangoes are produced and need to be evaluated for quality assessments. Presently, the quality inspection was done manually by the quality expert as there are no automated grading system is available. Hence, by automating the procedure as well as developing new classification technique, it may solve these problems. This thesis presents the new method on the high level features fusion of visible and IR Thermal Image features for mango quality assessment. A shape and weight analysis was developed from visible imaging and a maturity analysis was developed from IR thermal imaging. A Fourier-Descriptor method was developed to grade mango by its shape and a cylinder analysis method was used to grade Harumanis mango by its weight and it give different accuracy result of classification. The spectrum of infrared image was used to distinguish and classify the level of maturity of the fruits and it gave low accuracy compare to shape and weight classification. To get high accuracy for quality assessment for Harumanis mango, high level data fusion was proposed. This method combined all three classifier of shape, weight and maturity and it was found to be able to achieve 98% accuracy classification. 2017 2021-12-16T04:46:59Z 2021-12-16T04:46:59Z Thesis http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72933 en Universiti Malaysia Perlis (UniMAP) Universiti Malaysia Perlis (UniMAP) School of Mechatronic Engineering |
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Universiti Malaysia Perlis |
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Harumanis mango Optical communication Harumanis Harumanis -- Quality inspection Machine Vision |
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Harumanis mango Optical communication Harumanis Harumanis -- Quality inspection Machine Vision Fathinul Syahir, Ahmad Sa'ad Harumanis mango quality assessments technique based on high level features fusion of infra-red thermal and optical image |
description |
Doctor of Philosophy in Mechatronic Engineering |
author2 |
Ali Yeon, Md. Shakaff, Prof. Dr. |
author_facet |
Ali Yeon, Md. Shakaff, Prof. Dr. Fathinul Syahir, Ahmad Sa'ad |
format |
Thesis |
author |
Fathinul Syahir, Ahmad Sa'ad |
author_sort |
Fathinul Syahir, Ahmad Sa'ad |
title |
Harumanis mango quality assessments technique based on high level features fusion of infra-red thermal and optical image |
title_short |
Harumanis mango quality assessments technique based on high level features fusion of infra-red thermal and optical image |
title_full |
Harumanis mango quality assessments technique based on high level features fusion of infra-red thermal and optical image |
title_fullStr |
Harumanis mango quality assessments technique based on high level features fusion of infra-red thermal and optical image |
title_full_unstemmed |
Harumanis mango quality assessments technique based on high level features fusion of infra-red thermal and optical image |
title_sort |
harumanis mango quality assessments technique based on high level features fusion of infra-red thermal and optical image |
publisher |
Universiti Malaysia Perlis (UniMAP) |
publishDate |
2017 |
url |
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/72933 |
_version_ |
1724609973856501760 |
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13.214268 |