Efficient image segmentation and its application to motion estimation

In this paper, a new concept is introduced for economy image segmentation applicable in an earlier designed object based motion estimation algorithm. The image segmentation is based on simple features, like average grayscale within a segment, and uses spatial-temporal predictions in order to economize the segmentation procedure. Focus is on the segmentation process and the robust application of a non-perfect segmentation mask in the object based motion estimator. In this application, the new image segmentation method helps to improve the motion segmentation, while reducing the operations count. The paper describes both the object-based motion estimation and the block-based image segmentation. Experimental results are described in order to proof the validity of the concept.