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A fast way to locate the item regions of gray level images of cheques

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A fast way to locate the item regions of gray level images of cheques

Li, Zheng (2001) A fast way to locate the item regions of gray level images of cheques. Masters thesis, Concordia University.

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Abstract

In the business transactions of large corporations such as utility companies and banks, many cheques are being processed on a regular basis. Automatic reading of bank cheques is an active topic in Document Analysis. A machine capable of reading bank cheques will have wide applications in banks and those companies where huge quantities of cheques have to be processed. To realize such a system, many image processing, pattern recognition and OCR techniques must be involved. However, to develop an effective item extraction system is a difficult task, especially when the cheques contain complicated and colourful background pictures. In this thesis, a novel approach is proposed to locate the baselines of the cheque quickly and efficiently from a grey-scale cheque image. Based on that, we can extract the items such as the legal amount; courtesy amount and date respectively via a layout-driven extraction method. We have developed a system that can extract cheque items effectively and automatically combining all the current methods. The result is quite encouraging and a reliability of 98% has been achieved when tested on IRIS database which contains 600 gray-level cheque images. The performance analysis also indicates that our program is less time-consuming than the existing extraction system

Divisions:Concordia University > Faculty of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (Masters)
Authors:Li, Zheng
Pagination:x, 74 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:Theses (M.Comp.Sc.)
Program:Computer Science and Software Engineering
Date:2001
Thesis Supervisor(s):Suen, Ching Y
ID Code:1370
Deposited By:Concordia University Libraries
Deposited On:27 Aug 2009 13:18
Last Modified:08 Dec 2010 10:20
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