Intelligent forms processing system
Machine Vision and Applications - Special issue: document image analysis techniques
Extraction of data from preprinted forms
Machine Vision and Applications - Special issue: document image analysis techniques
Form Registration: A Computer Vision Approach
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Fast Registration of Tabular Document Images Using the Fourier-Mellin Transform
DIAL '04 Proceedings of the First International Workshop on Document Image Analysis for Libraries (DIAL'04)
Digital Ink to Form Alignment for Electronic Clipboard Devices
DAS '08 Proceedings of the 2008 The Eighth IAPR International Workshop on Document Analysis Systems
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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. The proposed method has been tested successfully with a high recognition rate on a set of 30 form templates. It is actually implemented on a real world application, in collaboration with an industrial partner who is specialized in software tablet solutions. The experience learned from the application also illustrates that the performance of matching method is at a high level of satisfaction in the real world.