Extraction of data from preprinted forms
Machine Vision and Applications - Special issue: document image analysis techniques
Geometric Structure Analysis of Document Images: A Knowledge-Based Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning of Generalized Document Templates for Data Extraction
DAS '02 Proceedings of the 5th International Workshop on Document Analysis Systems V
Logical Structure Analysis of Document Images Based on Emergent Computation
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
DIAL '04 Proceedings of the First International Workshop on Document Image Analysis for Libraries (DIAL'04)
Bibliographic Meta-Data Extraction Using Probabilistic Finite State Transducers
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
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We propose an algorithm for automatically generating metadata extraction parameters. It first enumerates candidates on the basis of metadata occurrence in training documents, and then examines these candidates to avoid side effects and to maximize effectiveness. This two-stage approach enables both avoidance of exponential explosion of computation and detailed optimization. An experiment on Japanese business documents shows that an automatically generated parameter enables metadata extraction as accurately as a manually adjusted one.