We present a method for extracting boundary surfaces from segmented cross-section image data. We use a constrained Potts model to interpolate an arbitrary number of region boundar...
Scott E. Dillard, John F. Bingert, Dan Thoma, B...
We present a new segmentation algorithm based on probabilistic histograms and introduce certainty calculus and certainty color maps to solve the difficult problem of histogram sep...
In this paper, a colour text/graphics segmentation is proposed. Firstly, it takes advantage of colour properties by computing a relevant hybrid colour model. Then an edge detectio...
Abstract. The semantic contextual information is shown to be an important resource for improving the scene and image recognition, but is seldom explored in the literature of previo...
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...