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ICIP
2001
IEEE

Image data mining from financial documents based on wavelet features

9 years 6 months ago
Image data mining from financial documents based on wavelet features
In this paper, we present a framework for clustering and classifying cheque images according to their payee-line content. The features used in the clustering and classificationprocesses are extracted from the wavelet domain by means of thresholding and counting of wavelet coeilficients. The feasibilityof this framework is tested on a database of 2620 cheque images. This database consists of cheques from 10 different accounts. Each account is written by a different person. Clustering and classification are performed separately on each account using distance-basedtechniques. We achieved coiiect-classificationrates of 86% and 81% for the supervised and unsupervised learning cases, respectively. These rates are the average of correct-classificationrates obtained from the 10different accounts.
Ossama El Badawy, Mahmoud R. El-Sakka, Khaled Hass
Added 25 Oct 2009
Updated 25 Oct 2009
Type Conference
Year 2001
Where ICIP
Authors Ossama El Badawy, Mahmoud R. El-Sakka, Khaled Hassanein, Mohamed S. Kamel
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