Paper
14 April 1993 Very fast recognition of GIRO check forms
Thien Minh Ha, Horst Bunke
Author Affiliations +
Proceedings Volume 1906, Character Recognition Technologies; (1993) https://doi.org/10.1117/12.143611
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1993, San Jose, CA, United States
Abstract
Check forms are used by many people in daily life for money remittance. Surprisingly, the processing of these forms at banks and post offices is only partly automated. In this paper, we deal with a particular kind of form, viz., the GIRO checks used in Switzerland. We describe a fully automatic system which is able to recognize the following items on a GIRO check: the financial institution, the name and address of the receiver, and the account number. The complete recognition of a GIRO check is divided into two phases. In the first phase, the system performs a layout analysis in order to localize regions corresponding to various items on the check. The input gray-level image is first binarized and segmented using the X-Y-tree decomposition algorithm resulting in a list of atomic entities (e.g., individual characters). Each entity is then interpreted as part of an item (e.g., receiver's name), according to the knowledge about possible layouts of a form. All atomic entities belonging to the same item are grouped together and yield the location of that item. In the second phase, the localized items are separately binarized again and submitted to an OCR engine to obtain streams of characters that correspond to the items. We have tested the system on a large number of checks and the results are promising in terms of both computation time and recognition accuracy.
© (1993) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thien Minh Ha and Horst Bunke "Very fast recognition of GIRO check forms", Proc. SPIE 1906, Character Recognition Technologies, (14 April 1993); https://doi.org/10.1117/12.143611
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KEYWORDS
Optical character recognition

Image segmentation

Data modeling

Detection and tracking algorithms

Receivers

Binary data

Visualization

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