01219nas a2200193   4500000000100000000000100001008004100002260000900043653000900052653000800061653001900069653002500088100001800113700002300131245004900154300001200203490000700215520080300222       2006                            d  c200610aDSmT10aDST10aExperts fusion10aimage classification1 aArnaud Martin1 aChristophe Osswald00aHuman Expert Fusion for Image Classification  a122-1430 v203 a<p>In image classification, merging the opinion of several human experts is very important for different tasks such as the evaluation or the training. Indeed, the ground truth is rarely known before the scene imaging. We propose here different models in order to fuse the informations given by two or more experts. The considered unit for the classification, a small tile of the image, can contain one or more kind of the considered classes given by the experts. A second problem that we have to take into account, is the amount of certainty of the expert has for each pixel of the tile. In order to solve these problems we define five models in the context of the Dempster-Shafer Theory and in the context of the Dezert-Smarandache Theory and we study the possible decisions with these models.</p>