Palo Alto Research Center Inc.

Dashan Gao

Minh Binh Do

Haitham Hindi

Yizhou Wang

A computer-implemented system and method for retrieving a digital image through document image decomposition is provided. A stored digital image is retrieved. Generic visual features are extracted. The features are grouped into a primitive layer including word-graphs that each include words and features. The words are grouped into a layout layer including zone hypotheses that each include one or more of the words. Causal dependencies between the word-graphs and the zone hypotheses are expressed through zone models that include a joint probability defining a pair of probabilistic models generated through a learned binary edge classifier. Each pair of probabilistic models is expressed as an optimal set selection problem including a set of cost functions and constraints. The optimal set selection problem is evaluated through a heuristic search of the cost functions and constraints and a non-overlapping optimal set of the zone hypotheses is provided that characterize the stored digital image.

Computer-implemented system and method for recognizing patterns in a digital image through document image decomposition

A system and method for decomposing a digital image is provided. A digital image is represented as a word-graph, which includes words and visualized features, and zone hypotheses that group one or more of the words. Causal dependencies of the zone hypotheses are expressed through a learned generative zone model to which costs and constraints are assigned. An optimal set of the zone hypotheses are inferred, which are non-overlapping, through a heuristic search of the costs and constraints.

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Dashan Gao