Using spectral information and machine vision for bruise detection on peaches and apricots

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dc.contributor.author Garcia-Pardo, E.
dc.contributor.author Yang, Q.
dc.contributor.author Bull, C. R.
dc.contributor.author Zwiggelaar, Reyer
dc.date.accessioned 2008-03-13T10:39:34Z
dc.date.available 2008-03-13T10:39:34Z
dc.date.issued 1996
dc.identifier.citation Garcia-Pardo , E , Yang , Q , Bull , C R & Zwiggelaar , R 1996 , ' Using spectral information and machine vision for bruise detection on peaches and apricots ' Journal of Agricultural Engineering Research , vol 63 , no. 4 , pp. 323-332 . , 10.1006/jaer.1996.0035 en
dc.identifier.other PURE: 76154
dc.identifier.other dspace: 2160/537
dc.identifier.uri http://hdl.handle.net/2160/537
dc.description R. Zwiggelaar, Q. Yang, E. Garcia-Pardo and C.R. Bull, 'Using spectral information and machine vision for bruise detection on peaches and apricots', Journal of Agricultural Engineering Research 63 (4), 323-332 1996) en
dc.description.abstract This paper addresses the problem of detecting bruises on peaches and apricots using machine vision. Bruises were created in a controlled manner on freshly harvested sample fruits. The spectral reflectance characteristics of both bruised and non-bruised surfaces were measured and analysed. From the analyses, the appropriate wavelengths, at which the two types of surface are well separated, were determined. Subsequently spectral filters centred at these selected wavelengths were used for image capture. Image analysis algorithms were developed to detect bruises in images. The most successful methods of detecting bruises were found to be ratio and normalised difference imaging at two wavelengths. The success rate for bruise detection was approximately 65%. en
dc.format.extent 10 en
dc.language.iso eng
dc.relation.ispartof Journal of Agricultural Engineering Research en
dc.title Using spectral information and machine vision for bruise detection on peaches and apricots en
dc.type Text en
dc.type.publicationtype Article (Journal) en
dc.identifier.doi http://dx.doi.org/10.1006/jaer.1996.0035
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Vision, Graphics and Visualisation Group en
dc.description.status Peer reviewed en


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