relation: https://khub.utp.edu.my/scholars/11132/
title: Mango Shape Maturity Classification Using Image Processing
creator: Ahmad, K.A.B.
creator: Othman, M.
creator: Syed Abdullah, S.L.
creator: Rasidah Ali, N.
creator: Muhamat Dawam, S.R.
description: This paper aim to apply image processing techniques to identify the degree of maturity in Harumanis Mango based on shape. At present, physical characteristics is the most important feature in determining fruit maturity. It is assessed by analyzing its external features such as colour, shape, size and texture. These features may not be applicable to certain types of fruits. This is the case for Harumanis mangoes, as size and colour does not determine its maturity. Here, it is the shape of the mango that plays a vital role for maturity and quality measurement. However, manual observations in determining fruit's maturity is too subjective and inconsistent. Hence, the computer vision method (CVM) was adopted, which involved image acquisition, pre-processing, segmentation, feature extraction and classification. For validation, experts assessment were sought where findings showed that the classification of CVM for maturity stage based on shape was consistent with human vision. © 2019 IEEE.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2019
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Ahmad, K.A.B. and Othman, M. and Syed Abdullah, S.L. and Rasidah Ali, N. and Muhamat Dawam, S.R.  (2019) Mango Shape Maturity Classification Using Image Processing.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083173351&doi=10.1109%2fICRAIE47735.2019.9037776&partnerID=40&md5=24931d37aa0721d49803e582ad95f585
relation: 10.1109/ICRAIE47735.2019.9037776
identifier: 10.1109/ICRAIE47735.2019.9037776