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Shape classification of Sunshine mango using machine vision

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Bibliographic Details
Main Author: Nur Athirah, Mabasri
Other Authors: School of Bioprocess Engineering
Format: Other
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2022
Subjects:
Shape Classification
Sunshine Mango
Machine vision
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/73281
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spelling my.unimap-732812022-01-11T04:43:06Z Shape classification of Sunshine mango using machine vision Nur Athirah, Mabasri School of Bioprocess Engineering Shape Classification Sunshine Mango Machine vision Access is limited to UniMAP community. This thesis presents the application of machine vision to classify the shape regularity of sunshine mango. The algorithm were successfully developed and programmed for image processing and image acquisition and then the regular and misshapen mangoes were able to classify using discriminant analysis. Using the acquired images from mangoes with different shapes, some essential geometrical features such as length, width, perimeter, area, major axis and minor axis were extracted from each image. Four size-shape parameter, area ratio, aspect ratio, circularity and compactness were used to analyse the mangoes between regular and misshapen. Based on discriminant analysis, three size-shape parameter (area ratio, aspect ratio, and circularity) were found to be effective in differentiate the regular and misshapen of mangoes. Overall the algorithm from discriminant analysis were able to classify 74% success rate to differentiate the regular and misshapen mangoes. 2022-01-11T04:43:06Z 2022-01-11T04:43:06Z 2017-06 Other http://dspace.unimap.edu.my:80/xmlui/handle/123456789/73281 en Universiti Malaysia Perlis (UniMAP)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Shape Classification
Sunshine Mango
Machine vision
spellingShingle Shape Classification
Sunshine Mango
Machine vision
Nur Athirah, Mabasri
Shape classification of Sunshine mango using machine vision
description Access is limited to UniMAP community.
author2 School of Bioprocess Engineering
author_facet School of Bioprocess Engineering
Nur Athirah, Mabasri
format Other
author Nur Athirah, Mabasri
author_sort Nur Athirah, Mabasri
title Shape classification of Sunshine mango using machine vision
title_short Shape classification of Sunshine mango using machine vision
title_full Shape classification of Sunshine mango using machine vision
title_fullStr Shape classification of Sunshine mango using machine vision
title_full_unstemmed Shape classification of Sunshine mango using machine vision
title_sort shape classification of sunshine mango using machine vision
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2022
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/73281
_version_ 1724610025878454272
score 13.159267

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