Palm print verification based deep learning
Lubab H. Albak, Raid Rafi Omar Al-Nima, Arwa Hamid Salih
Abstract
In this paper, we consider a palm print characteristic which has taken wide attentions in recent studies. We focused on palm print verification problem by designing a deep network called a palm convolutional neural network (PCNN). This network is adapted to deal with two-dimensional palm print images. It is carefully designed and implemented for palm print data. Palm prints from the Hong Kong Polytechnic University Contact-free (PolyUC) 3D/2D hand images dataset are applied and evaluated. The results have reached the accuracy of 97.67%, this performance is superior and it shows that our proposed method is efficient.
Keywords
deep learning; palm print; pattern recognition;
DOI:
http://doi.org/10.12928/telkomnika.v19i3.16573
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