Shape classification of sunshine mango using machine vision /

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....

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Wedi'i Gadw mewn:
Manylion Llyfryddiaeth
Prif Awdur: Nur Athirah Binti Mabasri
Awdur Corfforaethol: Universiti Malaysia Perlis
Fformat: Traethawd Ymchwil Llyfr
Iaith:English
Cyhoeddwyd: Perlis, Malaysia School of Bioprocess Engineering, University Malaysia Perlis 2017
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Crynodeb: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.
Disgrifiad Corfforoll:x, 65 pages illustrations (some color) 2017
Llyfryddiaeth:Includes bibliographical references (pages 40-42)