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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Euisun Choi Jongseok Lee Joonhyun Yoon |
| Copyright Year | 2006 |
| Description | Author affiliation: Fundamental Tech. Res., Nautilus Hyosung Inc., Seoul (Euisun Choi; Jongseok Lee; Joonhyun Yoon) |
| Abstract | In this paper, we investigate an approach to feature extraction for bank note classification by exploiting the potential of wavelet transform. In the proposed method, high spatial frequency coefficients taken from the wavelet domain are examined to extract features. We first perform edge detection on bill images to facilitate the wavelet feature extraction. The construction of feature vectors is then conducted by thresholding and counting of wavelet coefficients. The proposed feature extraction method can be applied to classifying any kind of bank note. However, in this paper we examine Korean won bills of 1000, 5000 and 10000 won types. Experimental results with a set of 10,800 bill images show that the proposed feature extraction method provides a correct classification rate of 99% even by using the Euclidean minimum distance matching as classifier |
| Sponsorship | IEEE CPS |
| Starting Page | 934 |
| Ending Page | 937 |
| File Size | 279058 |
| Page Count | 4 |
| File Format | |
| ISBN | 0769525210 |
| ISSN | 10514651 |
| DOI | 10.1109/ICPR.2006.553 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-08-20 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Feature extraction Wavelet transforms Image edge detection Frequency Data mining Image resolution Wavelet domain Wavelet coefficients Counterfeiting Image analysis |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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