Publication:
Apple Sweetness Measurement by image processing technique

Simple item page
dc.contributor.authorTeerach Ittatiruten_US
dc.contributor.authorAkkarote Lekhalawanen_US
dc.contributor.authorWatcharapong Tangjitwattanakornen_US
dc.contributor.authorChomtip Pornpanomchaien_US
dc.contributor.otherMahidol Universityen_US
dc.date.accessioned2018-12-11T02:38:12Z
dc.date.accessioned2019-03-14T08:04:32Z
dc.date.available2018-12-11T02:38:12Z
dc.date.available2019-03-14T08:04:32Z
dc.date.issued2016-07-22en_US
dc.description.abstract© 2016 IEEE. This research paper developed a system which allows users to determine the sweetness level of apples by using an image of the flesh part of the apple. The system, developed based with MATLAB, consists of four main modules, namely - 1) Image Acquisition, 2) Image Preprocessing, 3) Sweetness Determination, and 4) Result Determination. Two color spaces are utilized as the judging criteria of this paper, which are RGB and HSV color spaces. An Artificial Neural Network (ANN) is used as the main technique of sweetness determination. The average result of this implementation is a sweetness level of 79.03%.en_US
dc.identifier.citationProceedings of the 2016 5th ICT International Student Project Conference, ICT-ISPC 2016. (2016), 182-185en_US
dc.identifier.doi10.1109/ICT-ISPC.2016.7519266en_US
dc.identifier.other2-s2.0-84991770095en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/43471
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84991770095&origin=inwarden_US
dc.subjectComputer Scienceen_US
dc.titleApple Sweetness Measurement by image processing techniqueen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84991770095&origin=inwarden_US

Files

Collections

Scopus 2016-2017