1. Detection and recognition of erasures in on-line captured paper forms
- Author
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Laurent Heutte, Alain Wiart, Thierry Paquet, Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes (LITIS), Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Université Le Havre Normandie (ULH), Normandie Université (NU), and industriel
- Subjects
Artificial neural network ,Computer science ,Speech recognition ,[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] ,On-line recognition ,020207 software engineering ,02 engineering and technology ,Speech processing ,ComputingMethodologies_PATTERNRECOGNITION ,Erasure characterization ,Artificial Intelligence ,Handwriting ,Signal Processing ,Word recognition ,0202 electrical engineering, electronic engineering, information engineering ,Erasure ,020201 artificial intelligence & image processing ,Upstream (networking) ,Erasure detection ,Forms ,Computer Vision and Pattern Recognition ,Line (text file) ,Pen based applications ,Software - Abstract
International audience; This paper presents a method to automatically locate and recognize erasures in on-line captured handwritten documents in order to avoid a subsequent misrecognition of characters and words. We offer a comprehensive definition of the ambiguous concept of erasure in handwriting that results in a more accurate characterization of the different types of erasures. Thanks to this characterization, a preprocessing step, placed upstream of the word recognition engine, enables to classify through an MLP each couple of connected strokes as being an erasure or not using a low-level feature set. We evaluate our system on a real handwritten document database and show how our system can be tuned to operate in accordance with various recognition engines thus leading to high performance in erasure detection and recognition.
- Published
- 2007