<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0//ENhttp://www.w3.org/TR/REC-html40/strict.dtd"><html><head><metaname="qrichtext"content="1"/><styletype="text/css">p,li{white-space:pre-wrap;}</style></head><bodystyle=" font-family:'Sans Serif'; font-size:9pt; font-weight:400; font-style:normal;"></style></head><bodystyle=" font-family:'Sans Serif'; font-size:9pt; font-weight:400; font-style:normal;"><palign="center"style=" margin-top:16px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:x-large; font-weight:600;"><spanstyle=" font-size:x-large;">Image SVM Classification</span></p><pstyle=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><spanstyle=" font-size:large;">Brief Description</span></p><pstyle=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">Performs a SVM classification of the input image according to a SVM model file.</p><pstyle=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><spanstyle=" font-size:large;">Tags</span></p><pstyle=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">Learning</p><pstyle=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><spanstyle=" font-size:large;">Long Description</span></p><pstyle=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;">This application performs a SVM image classification based on a SVM model file (*.svm extension) produced by the TrainSVMImagesClassifier application. Pixels of the output image will contain the class label decided by the SVM classifier. The input pixels can be optionnaly centered and reduced according to the statistics file produced by the ComputeImagesStatistics application. An optional input mask can be provided, in which case only input image pixels whose corresponding mask value is greater than 0 will be classified. The remaining of pixels will be given the label 0 in the output image.</p><pstyle=" margin-top:14px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:large; font-weight:600;"><spanstyle=" font-size:large;">Parameters</span></p><ul><li><pstyle=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><spanstyle=" font-family:'Courier New, courier'; font-weight:600;";>[param] Input Image (-in): </span>The input Image to classify.</p></li><li><pstyle=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><spanstyle=" font-family:'Courier New, courier'; font-weight:600;";>[param] Input Mask (-mask): </span>The mask allows restricting classification of the input image to the area where mask pixel values are greater than 0.</p></li><li><pstyle=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><spanstyle=" font-family:'Courier New, courier'; font-weight:600;";>[param] SVM Model file (-svm): </span>A SVM model file.</p></li><li><pstyle=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><spanstyle=" font-family:'Courier New, courier'; font-weight:600;";>[param] Statistics file (-imstat): </span>A XML file containing mean and standard deviation to center and reduce samples before classification.</p></li><li><pstyle=" margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;"><spanstyle=" font-family:'Courier New, courier'; font-weight:600;";>[param] Output Image (-out): </span>Output image labeled with class labels</p></li><li><pstyle="margin-top:0px;margin-bottom:0px;mar
