Thai Fruit Recognition System (TFRS)

dc.contributor.authorChomtip Pornpanomchaien_US
dc.contributor.authorKhomkhwan Srikeawen_US
dc.contributor.authorVoranun Harnpraserten_US
dc.contributor.authorKamonwan Promnurakkiten_US
dc.contributor.authorชมทิพ พรพนมชัยen_US
dc.contributor.otherMahidol University. Faculty of Information and Communication Technology
dc.date.accessioned2012-05-01T09:58:42Z
dc.date.accessioned2018-03-28T02:06:49Z
dc.date.available2012-05-01T09:58:42Z
dc.date.available2018-03-28T02:06:49Z
dc.date.issued2009
dc.descriptionThe First (ACM) International Conference on Internet Multimedia Computing and Service (ICIMCS 2009): Kunming Yunnan, China; 2009. p. 108-112.
dc.description.abstractThe main objective of this research is to develop a computer system that can recognize Thai fruit by using image processing techniques. Our system is called “Thai Fruit Recognition System (TFRS)”. The system consists of four major components, which are: 1) image acquisition, 2) image preprocessing, 3) recognition, and displaying result. We used three important features to recognize Thai fruit, which are RGB colors, size, and edge shape. The TFRS is trained system with 39 kinds of Thai fruit on 312 images. We test our system on 123 images of 39 kinds of fruit for a training dataset and 30 images of 10 kinds of fruit for an untraining dataset. The precision of our system is 93.50 percent for the training dataset and 86.67 percent for the un-training dataset. The average access time is 54.68 seconds per image.en_US
dc.identifier.doi10.1145/1734605.1734633
dc.identifier.isbn9781605588407
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/10437
dc.language.isoengen_US
dc.rights.holderThe ACM Digital Libraryen_US
dc.subjectThai Fruiten_US
dc.subjectFruit Extractionen_US
dc.subjectFruit Recognitionen_US
dc.titleThai Fruit Recognition System (TFRS)en_US
dc.typeProceeding Articleen_US
mods.location.urlhttp://dl.acm.org/citation.cfm?id=1734633

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