<?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%">SUROVY, P</style></author><author><style face="normal" font="default" size="100%">Ribeiro, N a.</style></author><author><style face="normal" font="default" size="100%">BRASIL, F</style></author><author><style face="normal" font="default" size="100%">Pereira, J S</style></author><author><style face="normal" font="default" size="100%">OLIVEIRA, M R G</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Method for evaluation of coarse cork oak root system by means of digital imaging</style></title><secondary-title><style face="normal" font="default" size="100%">Agroforestry Systems</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">coarse root system</style></keyword><keyword><style  face="normal" font="default" size="100%">Cork oak</style></keyword><keyword><style  face="normal" font="default" size="100%">digital image</style></keyword><keyword><style  face="normal" font="default" size="100%">image similarity</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.springerlink.com/index/10.1007/s10457-011-9378-3</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">82</style></volume><pages><style face="normal" font="default" size="100%">111 - 119</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Digital imaging is becoming a powerful tool for data storage and information retrieval. Image comparison and similarity evaluation has become part of the information market and it is today a common part of, for example, web search engines. The cork oak tree (Quercus suberL.), the dominant species of the ‘montado’ woodland system is, due to its cultural and socio-economic value, protected by law that prevents extensive destructive studies on an essential part of the tree—the root. Especially in the Mediterranean zone, where the water is the limiting growth factor, the root development studies are of signicant interest. In this work we present a method of using digital images for cork oak coarse root systems-evaluation by means of digital imaging. Acquired images of structural roots are processed automatically to prevent subjective decisions by the human observer. The performance of the method, its potential for semantic retrieval and similarity assessment is demonstrated, having as example eight young cork oak root systems, and critical issues for evaluation and conclusion-making, are discussed.</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></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%">Benkirane, Hatim</style></author><author><style face="normal" font="default" size="100%">Benslimane, Rachid</style></author><author><style face="normal" font="default" size="100%">Hachmi, M'Hamed</style></author><author><style face="normal" font="default" size="100%">Sesbou, Ahmed</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Possibilité de contrôle automatique de la qualité du liège par vision artificielle</style></title><secondary-title><style face="normal" font="default" size="100%">Ann. For. Sci.</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Classification</style></keyword><keyword><style  face="normal" font="default" size="100%">cork quality control</style></keyword><keyword><style  face="normal" font="default" size="100%">defect quantification</style></keyword><keyword><style  face="normal" font="default" size="100%">digital image</style></keyword><keyword><style  face="normal" font="default" size="100%">visual system</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2001</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2001///</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1051/forest:2001139</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">58</style></volume><pages><style face="normal" font="default" size="100%">455 - 465</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The quality control often requires some visual inspection systems for defects detection in industrial production. In such application, those systems offer more reliability and lower processing time than a human operator. So this paper aims to introduce an automatic procedure to quality control of cork bits used for quality estimation of cork stacks, which is based on digital image analysis techniques. This procedure tries to quantify defects density of cork bit and to classify them in different quality classes. Experimental results are presented in order to evaluate the performance of the proposed automatic procedure.</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue></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%">Benkirane, Hatim</style></author><author><style face="normal" font="default" size="100%">Benslimane, Rachid</style></author><author><style face="normal" font="default" size="100%">Hachmi, M'Hamed</style></author><author><style face="normal" font="default" size="100%">Sesbou, Ahmed</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Possibilité de contrôle automatique de la qualité du liège par vision artificielle</style></title><secondary-title><style face="normal" font="default" size="100%">Ann. For. Sci.</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Classification</style></keyword><keyword><style  face="normal" font="default" size="100%">cork quality control</style></keyword><keyword><style  face="normal" font="default" size="100%">defect quantification</style></keyword><keyword><style  face="normal" font="default" size="100%">digital image</style></keyword><keyword><style  face="normal" font="default" size="100%">visual system</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><volume><style face="normal" font="default" size="100%">58</style></volume><pages><style face="normal" font="default" size="100%">455-465</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The quality control often requires some visual inspection systems for defects detection in industrial production. In such application, those systems offer more reliability and lower processing time than a human operator. So this paper aims to introduce an automatic procedure to quality control of cork bits used for quality estimation of cork stacks, which is based on digital image analysis techniques. This procedure tries to quantify defects density of cork bit and to classify them in different quality classes. Experimental results are presented in order to evaluate the performance of the proposed automatic procedure.</style></abstract></record></records></xml>