3D MORPHOLOGICAL SEGMENTATION AND MOTION ESTIMATION FOR IMAGE SEQUENCES

In this paper a method for segmenting image sequences and its applicat ion for motion estimation are presented, This method is based on a thr ee-dimensional (3D) morphological segmentation. A 3D (i.e. two spatial dimensions plus time) approach,has advantages over a 2D one, as it pr oduces a coherent segmentation along the time dimension. Mathematical morphology is a very attractive tool for segmentation purposes because it deals with geometric features, such as size, shape, contrast or co nnectivity, which can be considered as object-oriented, and therefore segmentation-oriented features. The method proposed follows a purely t op-down procedure, i.e. it first produces a coarse segmentation in a f irst level and refines it in the following levels. The original image sequences are considered as functions defined on a 3D space. As a resu lt, it will directly segment 3D regions. Furthermore, a time-recursive approach is introduced in order to deal with interactive applications , thus avoiding the drawbacks of purely 3D methods. Sequence segmentat ion has many applications in image sequence processing. In this paper, its application for motion analysis is discussed. As the segmentation is performed in a three-dimensional space, the produced regions are c onnected components in this space which can be related with moving obj ects. This implies a complete knowledge about the position and shape o f every segmented object of the scene in every time section. From this information, an affine transformation is used within each connected c omponent in order to estimate the parameters of motion of every region .