English Version is Trial!

کاربران فارسی زبان لطفا به بخش فارسی مراجعه نمایند.

سیویلیکا به زبان فارسی

Advanced Search

Title
Author
(Last name)
Abstract
Keywords

About CIVILICA®

CIVILICA® provides professional papers published in national and international conferences.

This site is registered for BoomSazeh Construction Technology Development Co.

 

Contact Us:

Tel: 021-88008044

Email: Info [at]  CIVILICA [dot] com

 

 
Home Page E-mail us to: Info @ CIVILICA . com Tel: +98-21-88008044

ISSN 1735-5540   

 

Quick Search in Title, Abstract, and Keywords of Papers

Showing Abstract of Eroded Money Notes Recognition using Wavelet Transform

 
Links

[ Bug Reporting | Back | See this Article in Persian CIVILICA ]

Paper Details

[ Downloads: 1 | Abstract Viewed: 447 | Pages: 5 ]

Title

Eroded Money Notes Recognition using Wavelet Transform

Topic: Published Year: 1389
Presentation:
Published in:

[ 6th Iranian Conference on Machine Vision and Image Processing ]

Original Language: English Full Text Size: Not Available

 

Abstract of the Article

 

Note: English CIVILICA is in its Trial Period so Full Texts can not be provided! Persian users can download it here

Download This article in PDF format Eroded Money Notes Recognition using Wavelet Transform

 

Authors:

[ Fatemeh Daraee ] - Electrical and Computer Engineering Department, Semnan University, Semnan, Iran
[ Saeed Mozaffari ] -

 

Abstract:

Process of bank checks and money notes play an important role in today commercial society. Usually automatic teller machines (ATM) have problems with eroded money notes. In this paper we proposed a new method for worn out Farsi money notes recognition using their texture content and wavelet transform. First, with the help of face detection algorithm, the obverse of the money note is separated from its reverse side. Then, central part of the money note, containing texture is extracted. Finally, wavelet transform is applied to this region of interest (ROI) to extract some features. Some distance measures are utilized to classify the input money note into predefined groups according to minimum distance. To increase accuracy of the system, in the post processing step, we used courtesy amount of the money note and template matching technique. The experimental results have shown that system performance is 80% for eroded money notes recognition.

 

Keywords:

money recognition, eroded money notes,wavelet transform.

 

CIVILICA® - © BoomSazeh Construction Technology Development Co.

SAVAFA