Abstract: Systems and methods for adjusting a camera parameter associated with a plurality of two-dimensional images are provided. Matched features can be selected as constraints for bundle adjustment using a graph model constructed based on the matched features. The graph model can have a plurality of nodes including a source node, a sink node, a point node for every matched feature, and a pose pair node associated with each pose pair viewing a matched feature. The graph model can include a plurality of edges interconnecting the plurality of nodes in the graph model. Each of these edges can be assigned a capacity and a cost based on various parameters. A flow can be computed through each of the edges of the graph model using, for instance, a minimum-cost maximum-flow algorithm. Matched features can be selected for bundle adjustment based on the flows of the edges in the graph model.

Abstract: A method and apparatus for comparing symbols extracted from binary images of text for classifying into equivalence classes. The present invention uses a Hausdorff-like method for comparing symbols for similarity. When a symbol contained in a bitmap A is compared to a symbol contained in a bitmap B, it is determined whether or not the symbol in bitmap B fits within a tolerance into a dilated representation of the symbol in bitmap A with no excessive density of errors and whether the symbol in bitmap A fits within a tolerance into a dilated representation of the symbol in bitmap B with no excessive density of errors. If both tests are passed, an error density check is performed to determine a match. The dilated representation of the bitmap accounts for various quantization errors that may occur along the boundaries of a symbol defined in the respective bitmaps. The dilation utilized preserves the topology of the symbol.