Abstract: A method for locating an object in an image is provided for an object that exhibits, in at least one direction, foreground pixel runs and background pixel runs consistent with at least characteristic of the object. In one embodiment, the method includes the acts of defining a plurality of regions in the image, associating a metric with each of the regions, finding pixel runs in the image, and identifying at least one pixel run in one of the plurality of regions where the at least one pixel run is consistent with the at least one characteristic of the object. According to one embodiment, the method includes the acts of adjusting the metric associated with the region where the at least one pixel run is identified and identifying, from among the plurality of regions, a region where the object is located based on a metric determined for a plurality of regions. In various embodiments, the object includes a repetitive pattern such as those found in barcodes and character strings.

Abstract: A method of pattern matching for recognition of objects within an image, uses a model defined by a set of one or more model primitives representative of large scale structures of an archetype. The image is analyzed to derive at least one target primitive representative of a large scale structure of the image. A basis is derived from at least one of the target primitives, and each of the target primitives represented as invariants in the derived basis. For each target primitive, any model primitives that at least partially match the target primitive are identified. Each identified model primitive is then processed to calculate a figure of merit indicative of a degree of correspondence between the target primitive and the model primitive. In some embodiments, the figure of merit is an Orthogonal projection between the target and model primitives, which is and accumulated for each model basis.

Abstract: A method of pattern matching for recognition of objects within an image, uses a model defined by a set of one or more model primitives representative of large scale structures of an archetype. The image is analyzed to derive at least one target primitive representative of a large scale structure of the image. A basis is derived from at least one of the target primitives, and each of the target primitives represented as invariants in the derived basis. For each target primitive, any model primitives that at least partially match the target primitive are identified. Each identified model primitive is then processed to calculate a figure of merit indicative of a degree of correspondence between the target primitive and the model primitive. In some embodiments, the figure of merit is an Orthogonal projection between the target and model primitives, which is and accumulated for each model basis.

Abstract: A method of pattern matching for recognition of objects within an image, uses a model defined by a set of one or more model primitives representative of large scale structures of an archetype. The image is analyzed to derive at least one target primitive representative of a large scale structure of the image. A basis is derived from at least one of the target primitives, and each of the target primitives represented as invariants in the derived basis. For each target primitive, any model primitives that at least partially match the target primitive are identified. Each identified model primitive is then processed to calculate a figure of merit indicative of a degree of correspondence between the target primitive and the model primitive. In some embodiments, the figure of merit is an Orthogonal projection between the target and model primitives, which is and accumulated for each model basis.

Abstract: A method of pattern matching for recognition of objects within an image, uses a model defined by a set of one or more model primitives representative of large scale structures of an archetype. The image is analyzed to derive at least one target primitive representative of a large scale structure of the image. A basis is derived from at least one of the target primitives, and each of the target primitives represented as invariants in the derived basis. For each target primitive, any model primitives that at least partially match the target primitive are identified. Each identified model primitive is then processed to calculate a figure of merit indicative of a degree of correspondence between the target primitive and the model primitive. In some embodiments, the figure of merit is an Orthogonal projection between the target and model primitives, which is and accumulated for each model basis.