Automatic and precise extraction of generic objects using saliency-based priors and contour constraints

This paper deals with automatic video segmentation without supervision or interactions. We examine a method for automatic noise reduction in segmented video frames utilizing contour information, which we have dubbed the Contour-Classification method. This method uses information about the contours of the segmented image mask in order to accurately reduce noise in segmented video frames. We will also examine which we have developed, called the Erosion-Dilation method. Our proposed method is then composed of these two fundamental techniques: Contour-Classification and Erosion-Dilation. Test results indicate our proposed method precisely removes noise regions from videos with low error rate when compared with both the original unaltered segmentation result and the Erosion-Dilation method.