Form analysis and understanding based on knowledge

Forms are different from common documents and more difficult to process. It is not very well done if processed by traditional document analyzing technology. The purpose of this thesis is to research on the key technologies of form analysis and understanding aiming at forms which are multi-type, large quantity, noisy, and variety of paper quality used by bank and revenue in our country. Based on analyzing knowledge of forms, a model of form based on object-orient sorting tree knowledge base and triple node representation is put forward. As for form feature extraction, hierarchical regulated hit or miss transform (HRHMT) is proposed. Feature extraction algorithm is also given. The algorithm is proved to be feasibility theoretically. Analysis on theoretical complexity and experiments shows their efficiency and superiority.