Erasure Extraction in On-Line Captured Paper Forms

In this paper, we describe a preprocessing system which locates erasures in on-line captured handwritten documents. Our approach is conceived so as to be placed upstream of the handwritten recognition engine. This system classifies each couple of connected strokes using a low level feature set and a multi layer perceptron classifier. One part of this study gives an efficient definition of erasure, which results in splitting the two original classes of the problem into nineteen more accurate sub-classes. The tunable tolerance level of the system provides a good flexibility to operate in accordance with various recognition engines. We evaluate our system on a real document database and present encouraging performance results.