INFORMys: A Flexible Invoice-Like Form-Reader System
IEEE Transactions on Pattern Analysis and Machine Intelligence
DAS '02 Proceedings of the 5th International Workshop on Document Analysis Systems V
smartFIX: A Requirements-Driven System for Document Analysis and Understanding
DAS '02 Proceedings of the 5th International Workshop on Document Analysis Systems V
A framework for validating recognized results in understanding table-form document images
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
A Recognition Method for Touching Japanese Handwritten Characters
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
A Recursive Analysis for Form Cell Recognition
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Issues in Developing a Commercial Parcel Reading System
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Case-Based Reasoning for Invoice Analysis and Recognition
ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Filled-in document identification using local features and a direct voting scheme
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
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Form reading technology based on form-typeidentification and form-data recognition is proposed. Thistechnology can solve difficulties in variety for readingdifferent items on fairly large number of different types offorms. The form-type identification consists of two parts:(i) extraction of targets such as important keywords in aform by matching between recogised characters and wordstrings in a keyword dictionary, and (ii) analysis ofpositional or semantic relationship between the targets byconstellation matching between these targets and wordlocation information in the keyword dictionary. The formdatarecognition consists of two parts: (i) extraction of aregion of interest (ROI) contained a character string of theitem by using a layout knowledge of the very form-type,and (ii) character string recognition of the item by usingthe linguistic constraint which can be obtained from acontent knowledge of the form-type. A experiment using642 sample forms with 107 different types in totalconfirmed that the form-type identification method cancorrectly identify 97% of 642 form samples at a rejectionrate 3%. Another experiment confirmed that the form-data recognition method can correctly read 95% of thenumber of items on the form samples.