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This paper describes 2(CREM), a recognition method to be applied on documents with complex structures allowing incremental learning in an interactive environment. The classification is driven by a model, which contains a static as well as a dynamic part and evolves by use. The first prototype of 2(CREM) has been tested on four different phases of newspaper image analysis: line segment recognition, frame recognition, line merging into blocks, and logical labeling. Some promising experimental results are reported.

Configuration REcognition Model for Complex Reverse Engineering Methods: 2(CREM)