Abstract: Disclosed is a method for the detection of the relative depth of two neighboring regions in relative motion with respect to each other in two images obtained from different shots of a scene, in order to know the composition of the scene. The method consists in carrying out a spatial segmentation of one of the images, called a reference image; a local estimation of the motion between the two images, the resultant vector field of which is called local motion; a determining of the motion estimation errors along the motion boundaries; and an analysis of the localization of the motion estimation errors along the motion boundaries to conclude that a region A is in front of a region B when the motion estimation error along the boundary is chiefly localized on the side B of this boundary.

Abstract: The invention relates to a method and system for coding segmented pictures, and to corresponding decoding method and system. In the coding system, a first sub-system defines the time evolution of said segmented pictures, or partitions, and a second one encodes both contours and textures of the regions of the successive partitions. The time evolution definition leads to a partition tree (PT) from which regions are extracted during an analysis step (AS) in order to form a decision tree (DT). A decision operation allows to select during a choice step (CS) distinct regions R.sub.S from various levels of said partition tree, in order to construct an optimal final partition (BFP) and, simultaneously, to choose the coding technique (BCT) that is the best one for each region of said optimal partition. Reciprocally the decoding method and system comprise means for defining the coding strategy chosen for each of said regions and decoding correspondingly the coded information.

Abstract: A method for processing images using hierarchically organized queues is provided. In particular, the method relates to the segmentation and filtering of certain shapes whose contours appear to be imprecise due to the existence of image noise, thereby eliminating such noise and providing a more precise image. The disclosed method is applicable to all sectors of image analysis and is especially useful in the analysis of images acquired by tomographs used in the medical field, whether these images are two-, three- or even four-dimensional. The method can also be extended to numerous dimensions and to color images. The method is also of particular usefulness in the fields of traffic control, i.e., detection of vehicles and roads, and more generally to all fields of industrial vision. The disclosed method can also be essential in coding and image compression for telecommunications and archiving.

Abstract: The transformation applies to images defined by pixels each presenting a characteristic, such as a brightness, defined by a digital value, with the pixels being distributed according to a matrix and their relations and distances established by a neighborhood graph. All or part of the image is explored according to a predetermined exploration mode and the value of each pixel is modified as a function of the values of a set of associated pixels, assuming their value in at least the image and being located inside a sliding window related to the pixel to be transformed, identical for all pixels and constituting a structuring element. The transformed version of each pixel is immediately substituted for the preceding value in an image memory. To implement the process, a device can be utilized having a morphological opening processor, an image memory and a morphological processor with rewrite processing.