Development of an inexpensive computer vision system for grading oyster meats

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dc.contributor.authorAwa, Teck Wahen
dc.contributor.committeechairByler, Richard K.en
dc.contributor.committeememberDiehl, Kenneth C.en
dc.contributor.committeememberShanholtz, Vernon O.en
dc.contributor.departmentAgricultural Engineeringen
dc.date.accessioned2014-03-14T21:40:31Zen
dc.date.adate2010-07-15en
dc.date.available2014-03-14T21:40:31Zen
dc.date.issued1988-05-05en
dc.date.rdate2010-07-15en
dc.date.sdate2010-07-15en
dc.description.abstractThe objective of this study was to develop an inexpensive automated device for grading raw oyster meats. The automation technique chosen was digital imaging. Typically, a computer vision system contains a microcomputer and a digital camera. An inexpensive digital camera connected to a personal computer was used to measure the projected area of the oyster meats. Physical characteristics of the oyster meats were important in designing a computer vision grading system and the necessary data were not found in the literature. Selected physical characteristics of oyster meats, including the projected area, weight, height, and volume were measured by independent methods. The digital image areas were found to be highly correlated to oyster meat volumes and weights. Currently oysters are marketed on the basis of volume. The results from this study indicated that the relationship between the oyster meat area as measured by computer vision and volume can be used as a grading criterion. The oysters ranged in volume from 3.5 cm³ to 19.4 cm³ A three dimensional image was not required because the height was not important. Tests showed that the system was consistent and successfully graded 5 oysters per second. The system was calibrated, and the prediction equation was validated with an estimated measurement error of ± 3.04 cm³ at a 95% confidence level. The development of automated graders using digital imaging techniques could help improve the quality and consistency of the graded oyster meats.en
dc.description.degreeMaster of Scienceen
dc.format.extentx, 145 leavesen
dc.format.mediumBTDen
dc.format.mimetypeapplication/pdfen
dc.identifier.otheretd-07152010-020219en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-07152010-020219/en
dc.identifier.urihttp://hdl.handle.net/10919/43742en
dc.publisherVirginia Techen
dc.relation.haspartLD5655.V855_1988.A842.pdfen
dc.relation.isformatofOCLC# 18523919en
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subject.lccLD5655.V855 1988.A842en
dc.subject.lcshImage processing -- Digital techniquesen
dc.subject.lcshOystersen
dc.titleDevelopment of an inexpensive computer vision system for grading oyster meatsen
dc.typeThesisen
dc.type.dcmitypeTexten
thesis.degree.disciplineAgricultural Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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