Fingerprints Authentication Using Grayscale Fractal Dimension


  • Nadia. M. G. Alsaidi Department of Applied Sciences, University of Technology, IRAQ
  • Arkan J. Mohammed Department of Mathematics, College of Science, Mustansiriyah University, IRAQ
  • Wael J. Abdulaal Department of Applied Sciences, University of Technology, IRAQ



Fractal Dimension, Box Counting, Fingerprint, Authentication


Characterizing of visual objects is an important role in pattern recognition that can be performed through shape analysis. Several approaches have been introduced to extract relevant information of a shape. The complexity of the shape is the most widely used approach for this purpose where fractal dimension and generalized fractal dimension are methodologies used to estimate the complexity of the shapes. The box counting dimension is one of the methods that used to estimate fractal dimension. It is estimated basically to describe the self-similarity in objects. A lot of objects have the self-similarity; fingerprint is one of those objects where the generalized box counting dimension is used for recognizing of the fingerprints to be utilized for authentication process. A new fractal dimension method is proposed in this paper. It is verified by the experiment on a set of natural texture images to show its efficiency and accuracy, and a satisfactory result is found. It also offers promising performance when it is applied for fingerprint recognition.


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How to Cite

N. M. G. Alsaidi, A. J. Mohammed, and W. J. Abdulaal, “Fingerprints Authentication Using Grayscale Fractal Dimension”, MJS, vol. 29, no. 3, pp. 106–112, Mar. 2019.