Issue No. 11 - November (1996 vol. 18)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.544084
<p><b>Abstract</b>—Recent advances in intelligent character recognition are enabling us to address many challenging problems in document image analysis. One of them is intelligent form analysis. This paper describes a generic system for form dropout when the filled-in characters or symbols are either touching or crossing the form frames. We propose a method to separate these characters from form frames whose locations are unknown. Since some of the character strokes are either touching or crossing the form frames, we need to address the following three issues: 1) localization of form frames; 2) separation of characters and form frames; and 3) reconstruction of broken strokes introduced during separation. The form frame is automatically located by finding long straight lines based on the block adjacency graph. Form frame separation and character reconstruction are implemented by means of this graph. The proposed system includes form structure learning and form dropout. First, a form structure-based template is automatically generated from a blank form which includes form frames, preprinted data areas and skew angle. With this form template, our system can then extract both handwritten and machine-typed filled-in data. Experimental results on three different types of forms show the performance of our system. Further, the proposed method is robust to noise and skew that is introduced during scanning.</p>
Form processing, learning form structure, document image analysis, segmentation, character reconstruction, block adjacency graph.
A. K. Jain and B. Yu, "A Generic System for Form Dropout," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 18, no. , pp. 1127-1134, 1996.