<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Costa, Augusta</style></author><author><style face="normal" font="default" size="100%">Pereira, Helena</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Decision rules for computer-vision quality classification of wine natural cork stoppers</style></title><secondary-title><style face="normal" font="default" size="100%">AMERICAN JOURNAL OF ENOLOGY AND VITICULTURE</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">canonical discriminant</style></keyword><keyword><style  face="normal" font="default" size="100%">quality classes</style></keyword><keyword><style  face="normal" font="default" size="100%">wine cork stoppers</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2006///</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">57</style></volume><pages><style face="normal" font="default" size="100%">210 - 219</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Image-analysis techniques were applied to the surface of wine cork stoppers (tops and bodies) of the standard seven commercial quality classes to characterize their porosity. Canonical discriminant analysis (CDA) and stepwise discriminant analysis (SDA) were used to differentiate quality class and to identify the best features to select these classes. The accuracy of classification using CDA functions was on average greater than 50% for the seven commercial classes and was greater than 67% for a simplified three-grade classification. Based on the independent variables of the first CDA function determined by the stepwise method, a set of features was selected for use in decision rules for cork stopper classification: porosity coefficient and maximum pore dimensions (length and area) for bodies and porosity coefficient and number of pores for tops. Threshold limits for each feature were established for each quality class and a classification algorithm was applied. Results showed an overall match in class yield of 86% and better class homogeneity and separation. These are proposed as a foundation for future standardization of cork stopper classification based on image analysis and computerized vision systems selection of quantified features to ensure uniformity and transparency in trade while maintaining the overall economical feasibility in industrial processing.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><notes><style face="normal" font="default" size="100%">The following values have no corresponding Zotero field:&lt;br/&gt;pub-location: PO BOX 1855, DAVIS, CA 95617-1855 USA&lt;br/&gt;publisher: AMER SOC ENOLOGY VITICULTURE</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Costa, A.</style></author><author><style face="normal" font="default" size="100%">Pereira, H.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Quality characterization of wine cork stoppers using computer vision</style></title><secondary-title><style face="normal" font="default" size="100%">JOURNAL INTERNATIONAL DES SCIENCES DE LA VIGNE ET DU VIN</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">computer imaging</style></keyword><keyword><style  face="normal" font="default" size="100%">quality classes</style></keyword><keyword><style  face="normal" font="default" size="100%">wine cork stoppers</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2005///</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">209 - 218</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Image analysis techniques were applied on the surface of wine cork stoppers (tops and lateral cylindrical surface) of seven commercial quality classes to characterize their porosity. An increasing trend from the best to the worst quality classes was found for features related to area of pores (i.e. maximum length and width or pore maximum area) and concentration variables (i.e. porosity coefficient or number of pores per 100 cm(2)). Shape variables were rather constant and mean values showed no differences between quality classes. Variation of the pores characteristics within each quality class was large especially in the mid-quality range. Therefore there were no statistically significant differences to allow the isolation of the all quality classes and overlapping was particularly important in the medium-quality classes. The reduction of grading into only three quality classes allowed to isolate statistically different subsets based on porosity coefficient and number of pores per 100 cm(2). These variables can be selected for further development into quality grades specification of wine cork stoppers.</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue><notes><style face="normal" font="default" size="100%">The following values have no corresponding Zotero field:&lt;br/&gt;pub-location: 42 RUE MARSAN, 33300 BORDEAUX, FRANCE&lt;br/&gt;publisher: VIGNE ET VIN PUBLICATIONS INT</style></notes></record></records></xml>