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Shape-based sorting of agricultural produce using support vector machines in a MATLAB/SIMULINK environment

The ability to sort agricultural produce automatically is very important. This paper addresses one way to identify agricultural produce based on their shape. The techniques used are based on support vector machines. The images of the produce are loaded into MATLAB and the features extracted using im...

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Main Authors: Kyaw, M.M., Ahmed, S.K., Md Sharrif, Z.A.
Format: Conference Paper
Language:English
Published: 2017
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spelling my.uniten.dspace-50352017-11-14T07:50:18Z Shape-based sorting of agricultural produce using support vector machines in a MATLAB/SIMULINK environment Kyaw, M.M. Ahmed, S.K. Md Sharrif, Z.A. The ability to sort agricultural produce automatically is very important. This paper addresses one way to identify agricultural produce based on their shape. The techniques used are based on support vector machines. The images of the produce are loaded into MATLAB and the features extracted using image processing techniques based on edge detection. These features are then input to a classifier; i.e., a support vector machine, for identification. A regular digital camera is used for acquiring the image, and all manipulations are performed in a MATLAB / SIMULINK environment. The results obtained are an improvement over a previous technique. ©2009 IEEE. 2017-11-14T03:21:32Z 2017-11-14T03:21:32Z 2009 Conference Paper 10.1109/CSPA.2009.5069203 en Proceedings of 2009 5th International Colloquium on Signal Processing and Its Applications, CSPA 2009 2009, Article number 5069203, Pages 135-139
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/
language English
description The ability to sort agricultural produce automatically is very important. This paper addresses one way to identify agricultural produce based on their shape. The techniques used are based on support vector machines. The images of the produce are loaded into MATLAB and the features extracted using image processing techniques based on edge detection. These features are then input to a classifier; i.e., a support vector machine, for identification. A regular digital camera is used for acquiring the image, and all manipulations are performed in a MATLAB / SIMULINK environment. The results obtained are an improvement over a previous technique. ©2009 IEEE.
format Conference Paper
author Kyaw, M.M.
Ahmed, S.K.
Md Sharrif, Z.A.
spellingShingle Kyaw, M.M.
Ahmed, S.K.
Md Sharrif, Z.A.
Shape-based sorting of agricultural produce using support vector machines in a MATLAB/SIMULINK environment
author_facet Kyaw, M.M.
Ahmed, S.K.
Md Sharrif, Z.A.
author_sort Kyaw, M.M.
title Shape-based sorting of agricultural produce using support vector machines in a MATLAB/SIMULINK environment
title_short Shape-based sorting of agricultural produce using support vector machines in a MATLAB/SIMULINK environment
title_full Shape-based sorting of agricultural produce using support vector machines in a MATLAB/SIMULINK environment
title_fullStr Shape-based sorting of agricultural produce using support vector machines in a MATLAB/SIMULINK environment
title_full_unstemmed Shape-based sorting of agricultural produce using support vector machines in a MATLAB/SIMULINK environment
title_sort shape-based sorting of agricultural produce using support vector machines in a matlab/simulink environment
publishDate 2017
_version_ 1644493596376694784
score 13.222552

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