Fingerprint Feature Extraction with Artificial Neural Network and Image Processing Methods

  • Maciej SzymkowskiEmail author
  • Khalid Saeed
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 889)


Fingerprints are often claimed as the safest measurable human trait. As one can observe they are commonly used in many different solutions. Nowadays they are applied for instance in financial institutions where clients can confirm their identities with fingerprints. These biometrics are the kind of the password that no one can lost or forget. An approach to extract fingerprints features with artificial neural network and image processing algorithms is presented in this work. Soft computing methods are becoming more popular. It leads to their usage in the human recognition procedures. In the case of the algorithm presented in this paper, the results from neural network are confirmed by Crossing-Number (CN) algorithm. The two-step confirmation ensures more precise results than obtained with each of them separately. The final stage of the algorithm is minutiae extraction and marking them in the analyzed image.


Fingerprint Biometrics Physiological biometrics Artificial neural network Minutiae detection 



This work was supported by grant S/WI/3/2018 from Białystok University of Technology and funded with resources for research by the Ministry of Science and Higher Education in Poland.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of Computer ScienceBialystok University of TechnologyBialystokPoland

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