Form recognition from ink strokes on tablet
De Cao Tran, Patrick Franco, Jean-Marc Ogier · 2010
This paper proposes a method for form recognition from handwritten input captured as digital ink on a tablet. Form recognition is an important step of form processing to read the data on a filled form. This type of recognition is different from traditional image matching (searching and retrieving) because the query image (data ink) has but few common characteristics with the retrieval images (i.e. form templates). The fact is that form structure is free in variation. It is not rare that two forms are very close in their structures and in semantic of fields. Filling in a form is also free in variation. The same form may be filled with different contents and in different ways of online context. The main idea for matching between ink strokes and form template in this paper is featureless, based on Bhattacharyya measure. The distance between the distribution of ink strokes and the distribution of form fields is the matching measure. These distributions are spatial information which is based on the crossing of coordinates of ink points and the crossing of fields to be filled. However, these coordinates are not taken on the same coordinate system. Ink point coordinates are based on the tablet coordinate system (differs from A4 format) while field coordinates are in paper size (for example, A4 format). In order to deal with this problem, affine transform is used to standardize the coordinate system. The coordinate system on the tablet is transformed into paper format system.