Name
Abstract | ||
|---|---|---|
We present in this paper a new general method, the Eyes Wide Open method (EWO) for the design of rule-based document recognition systems. Our contribution is to introduce a learning procedure, through machine learning techniques, in interaction with the user to design the recognition system. Therefore, and unlike many approaches that are manually designed, ours can easily adapt to a new type of documents while taking advantage of the expressiveness of rule-based systems and their ability to convey the hierarchical structure of a document. The EWO method is independent of any existing recognition system. An automatic analysis of an annotated corpus, guided by the user, is made to help the adaption of the recognition system to a new kind of document. The user will then bring sense to the automatically extracted information. In this paper, we validate EWO by producing two rule-based systems: one for the Maurdor international competition, on a heterogeneous corpus of documents, containing handwritten and printed documents, written in different languages and another one for the RIMES competition corpus, a homogeneous corpus of French handwritten business letters. On the RIMES corpus, our method allows an assisted design of a grammatical description that gives better results than all the previously proposed statistical systems. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s10032-017-0282-x | IJDAR |
Keywords | Field | DocType |
Document layout analysis, Rule inference, Rule based system, Clustering | Computer science,Natural language processing,Artificial intelligence,Cluster analysis,Expressivity,Interactive Learning,Rule-based system,Recognition system,Pattern recognition,Homogeneous,Document layout analysis,Document recognition,Machine learning | Journal |
Volume | Issue | ISSN |
20 | 2 | 1433-2825 |
Citations | PageRank | References |
1 | 0.35 | 19 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cérès Carton | 1 | 14 | 3.10 |
| Aurélie Lemaitre | 2 | 63 | 9.41 |
| Bertrand Coüasnon | 3 | 169 | 19.22 |