Personal Identification Using Palm Features Recognition

  • Hanaa Mahmood Dr.
  • Yahya Ismail Ibrahim
  • Nagham Tharwat Saeed
Keywords: FFNN, ROI, Score, Learning, Veins, NIR.


Personal recognition is meant for finding a way for establishment of connections between the person and his/her biometrical features. Such system is depending various data types such as facial images, voice and limbs. In this paper, palm print recognition is made using deep learning paradigms such as feed forward neural network (FFNN). The palm features are extracted by tracking the principal lines of palm skin. This involves performing of pixel to pixel analysis by comparing pixel value with its four sides neighbors. FFNN model is tuned up using ABC-KNN algorithm then used for classification.  The proposed system has yielded good recognition accuracy score of 98.66%.

How to Cite
Mahmood, H., Ismail Ibrahim , Y., & Tharwat Saeed , N. (2022). Personal Identification Using Palm Features Recognition. International Journal of Engineering Technology and Natural Sciences, 4(2), 102 - 110.