Abstract: The invention relates to a method for reversibly rendering at least one object in an image unrecognizable, whereby each object to be rendered unrecognizable is automatically detected in an original image and at least one data set is generated comprising image information for the representation of the image in which each object to be rendered unrecognizable is, in fact, rendered unrecognizable, and additional information that permits the restoration of each object that has been rendered unrecognizable in the image.

Abstract: A process for image analysis which includes selecting a number M of images, forming a model graph from each of the number of images, such that each model has a number N of nodes, assembling the model graphs into a gallery, and mapping the gallery of model graphs into an associated bunch graph by using average distance vectors &Dgr;ij for the model graphs as edge vectors in the associated bunch graph. A number M of jets is associated with each node of the associated bunch graph, and at least one jet is labeled with an attribute characteristic of one of the number of images. An elastic graph matching procedure is performed wherein the graph similarity function is replaced by a bunch-similarity function.

Abstract: The invention provides an apparatus, and related method, for providing a procedure to analyze images based on two-dimensional shape primitives. In the procedure, an object representation is created automatically from an image and then this representation is applied to another image for the purpose of object recognition. The features used for the representation are the two type of two-dimensional shape primitives: local line segments and vertices. Furthermore, the creation of object representations is extended to sequences of images, which is especially needed for complex scenes in which, for example, the object is presented in front of a structured background.

Abstract: A process for image analysis which includes selecting a number M of images, forming a model graph from each of the number of images, such that each model has a number N of nodes, assembling the model graphs into a gallery, and mapping the gallery of model graphs into an associated bunch graph by using average distance vectors &Dgr;ij for the model graphs as edge vectors in the associated bunch graph. A number M of jets is associated with each node of the associated bunch graph, and at least one jet is labeled with an attribute characteristic of one of the number of images. An elastic graph matching procedure is performed wherein the graph similarity function is replaced by a bunch-similarity function.

Abstract: A process for image analysis which includes selecting a number M of images, forming a model graph from each of the number of images, such that each model has a number N of nodes, assembling the model graphs into a gallery, and mapping the gallery of model graphs into an associated bunch graph by using average distance vectors &Dgr;ij for the model graphs as edge vectors in the associated bunch graph. A number M of jets is associated with each node of the associated bunch graph, and at least one jet is labeled with an attribute characteristic of one of the number of images. An elastic graph matching procedure is performed wherein the graph similarity function is replaced by a bunch-similarity function.