Detection and recognition of erasures in on-line captured paper forms

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.