Agricultural produce sorting and grading using support vector machines and fuzzy logic

Agriculture sector was accorded a very different treatment in the Ninth Malaysia Plan (9MP) where this sector is being revitalized to become a part of the economic growth engine. The Information and Communication Technology (ICT) application is going to be implemented as a solution in improving the...

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Main Authors: Mustafa N.B.A., Ahmed S.K., Ali Z., Yit W.B., Abidin A.A.Z., Md Sharrif Z.A.
Other Authors: 57191952020
Format: Conference Paper
Published: 2023
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spelling my.uniten.dspace-307902024-04-17T09:37:06Z Agricultural produce sorting and grading using support vector machines and fuzzy logic Mustafa N.B.A. Ahmed S.K. Ali Z. Yit W.B. Abidin A.A.Z. Md Sharrif Z.A. 57191952020 25926812900 25824589000 35319056300 25824750400 6507195893 Agricultural Produce Classification Fuzzy logic Grading Agricultural machinery Agricultural products Automation Cameras Economics Feature extraction Fuzzy systems Grading Image processing Imaging systems Support vector machines Telecommunication equipment Telephone systems Agricultural Produce Agriculture sectors Automated systems Classification Economic growths Fruit shape Grading process Information and Communication Technologies Malaysia Mobile phone cameras Fuzzy logic Agriculture sector was accorded a very different treatment in the Ninth Malaysia Plan (9MP) where this sector is being revitalized to become a part of the economic growth engine. The Information and Communication Technology (ICT) application is going to be implemented as a solution in improving the status of the agriculture sector. The idea of integrating ICT with agriculture sector motivates the development of an automated system for sorting and grading of agriculture produce. Currently, the grading is done based on observations and through experience. The developed system starts the grading process by capturing the fruit's image using a regular digital camera or mobile phone camera. Then, the image is transmitted to the processing level where feature extraction, classification and grading is done using MATLAB. In this paper, the focus is more on agricultural produce Sorting and Grading technique. The agricultural produce is classified based on fruit shape and size using Support Vector Machines (SVMs) and its grade is determined using Fuzzy Logic (FL) approach. The results obtained are very promising. Final 2023-12-29T07:53:20Z 2023-12-29T07:53:20Z 2009 Conference Paper 10.1109/ICSIPA.2009.5478684 2-s2.0-77954473782 https://www.scopus.com/inward/record.uri?eid=2-s2.0-77954473782&doi=10.1109%2fICSIPA.2009.5478684&partnerID=40&md5=4737bed92f118215697597b925d7c54e https://irepository.uniten.edu.my/handle/123456789/30790 5478684 391 396 Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Agricultural Produce
Classification
Fuzzy logic
Grading
Agricultural machinery
Agricultural products
Automation
Cameras
Economics
Feature extraction
Fuzzy systems
Grading
Image processing
Imaging systems
Support vector machines
Telecommunication equipment
Telephone systems
Agricultural Produce
Agriculture sectors
Automated systems
Classification
Economic growths
Fruit shape
Grading process
Information and Communication Technologies
Malaysia
Mobile phone cameras
Fuzzy logic
spellingShingle Agricultural Produce
Classification
Fuzzy logic
Grading
Agricultural machinery
Agricultural products
Automation
Cameras
Economics
Feature extraction
Fuzzy systems
Grading
Image processing
Imaging systems
Support vector machines
Telecommunication equipment
Telephone systems
Agricultural Produce
Agriculture sectors
Automated systems
Classification
Economic growths
Fruit shape
Grading process
Information and Communication Technologies
Malaysia
Mobile phone cameras
Fuzzy logic
Mustafa N.B.A.
Ahmed S.K.
Ali Z.
Yit W.B.
Abidin A.A.Z.
Md Sharrif Z.A.
Agricultural produce sorting and grading using support vector machines and fuzzy logic
description Agriculture sector was accorded a very different treatment in the Ninth Malaysia Plan (9MP) where this sector is being revitalized to become a part of the economic growth engine. The Information and Communication Technology (ICT) application is going to be implemented as a solution in improving the status of the agriculture sector. The idea of integrating ICT with agriculture sector motivates the development of an automated system for sorting and grading of agriculture produce. Currently, the grading is done based on observations and through experience. The developed system starts the grading process by capturing the fruit's image using a regular digital camera or mobile phone camera. Then, the image is transmitted to the processing level where feature extraction, classification and grading is done using MATLAB. In this paper, the focus is more on agricultural produce Sorting and Grading technique. The agricultural produce is classified based on fruit shape and size using Support Vector Machines (SVMs) and its grade is determined using Fuzzy Logic (FL) approach. The results obtained are very promising.
author2 57191952020
author_facet 57191952020
Mustafa N.B.A.
Ahmed S.K.
Ali Z.
Yit W.B.
Abidin A.A.Z.
Md Sharrif Z.A.
format Conference Paper
author Mustafa N.B.A.
Ahmed S.K.
Ali Z.
Yit W.B.
Abidin A.A.Z.
Md Sharrif Z.A.
author_sort Mustafa N.B.A.
title Agricultural produce sorting and grading using support vector machines and fuzzy logic
title_short Agricultural produce sorting and grading using support vector machines and fuzzy logic
title_full Agricultural produce sorting and grading using support vector machines and fuzzy logic
title_fullStr Agricultural produce sorting and grading using support vector machines and fuzzy logic
title_full_unstemmed Agricultural produce sorting and grading using support vector machines and fuzzy logic
title_sort agricultural produce sorting and grading using support vector machines and fuzzy logic
publishDate 2023
_version_ 1806427967386025984
score 13.222552