Banknote Classification Using Artificial Neural Network Approach

Ali Yasar; Esra Kaya; Ismail Saritas

doi:https://doi.org/10.18201/ijisae.55250

Makale detayları

Banknote Classification Using Artificial Neural Network Approach

Yazarlar:

Ali Yasar | Esra Kaya | Ismail Saritas

Yayıncı:

İsmail SARITAŞ

Dergi:

International Journal of Intelligent Systems and Applications in Engineering 2016 Vol.4 Issue 1, pp.16-19

Belge Tipi:

Makale

Yayın Tarihi:

3/2016

Belge Dili:

Türkçe

Document ID (Org No.):

2000817579

Sıklık:

Üç Aylık

eISSN:

2147-6799

DOI:

https://doi.org/10.18201/ijisae.55250

Özet:

 

In this study, clustering process has been performed using artificial neural network (ANN) approach on the pictures belonging to our dataset to determine if the banknotes are genuine or counterfeit.  Four input parameters, one hidden layer with 10 neurons and one output has been used for the ANN. All of these parameters were real-valued continuous. Data were extracted from images that were taken from genuine and forged banknote-like specimens. For digitization, an industrial camera usually used for print inspection was used. The final images have 400x 400 pixels. Due to the object lens and distance to the investigated object gray-scale pictures with a resolution of about 660 dpi were gained. Wavelet Transform tool were used to extractfeatures from images.  Four input parameters are processed in the hidden layer with 10 neurons and the output realizes the clustering process. The classification process of 1372 unit data by using ANN approach is sure to be a success as much as the actual data set. The regression results of the clustering process is considerably well. It is determined that the training regression is 0,99914, testing regression is 0,99786 and the validation regression is 0,9953, respectively. Based on the results obtained, it is seen that classification process using ANN is capable of achieving outstanding success.

Makale detayları

Banknote Classification Using Artificial Neural Network Approach

Yazarlar: Ali Yasar | Esra Kaya | Ismail Saritas

Yayıncı: İsmail SARITAŞ

Dergi: International Journal of Intelligent Systems and Applications in Engineering 2016 Vol.4 Issue 1, pp.16-19

Belge Tipi: Makale

Yayın Tarihi: 3/2016

Belge Dili: Türkçe

Document ID (Org No.): 2000817579

Sıklık: Üç Aylık

eISSN: 2147-6799

DOI: https://doi.org/10.18201/ijisae.55250

Sayı

Yazarlar:

Ali Yasar | Esra Kaya | Ismail Saritas

Yayıncı:

İsmail SARITAŞ

Dergi:

International Journal of Intelligent Systems and Applications in Engineering 2016 Vol.4 Issue 1, pp.16-19

Belge Tipi:

Makale

Yayın Tarihi:

3/2016

Belge Dili:

Türkçe

Document ID (Org No.):

2000817579

Sıklık:

Üç Aylık

eISSN:

2147-6799

DOI:

https://doi.org/10.18201/ijisae.55250