<?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%">Péter Balázs</style></author><author><style face="normal" font="default" size="100%">Zoltán Ozsvár</style></author><author><style face="normal" font="default" size="100%">Tamás Sámuel Tasi</style></author><author><style face="normal" font="default" size="100%">László G Nyúl</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Measure of Directional Convexity Inspired by Binary Tomography</style></title><secondary-title><style face="normal" font="default" size="100%">Fundamenta Informaticae</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Oct 2015</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">141</style></volume><pages><style face="normal" font="default" size="100%">151-167</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span&gt;Inspired by binary tomography, we present a measure of directional convexity of binary images combining various properties of the configuration of 0s and 1s in the binary image. The measure can be supported by proper theory, is easy to compute, and as shown in our experiments, behaves intuitively. &lt;/span&gt;&lt;span class=&quot;below-fold&quot; data-below-fold=&quot;FI1269&quot;&gt;The measure can be useful in numerous applications of digital image processing and pattern recognition, and especially in binary tomography. We show in detail an application of this latter one, by providing a novel reconstruction algorithm for almost hv-convex binary images. We also present experimental results and mention some of the possible generalizations of the measure. &lt;/span&gt;&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2-3</style></issue><work-type><style face="normal" font="default" size="100%">Journal article</style></work-type><section><style face="normal" font="default" size="100%">151</style></section></record></records></xml>