Fingerprint Image Segmentation Using Textural Features

  • Reji C. JoyEmail author
  • M. Azath
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 460)


Automatic Fingerprint Identification System (AFIS) uses fingerprint segmentation as its pre-processing step. A fingerprint segmentation step divides the fingerprint image into foreground and background. An AFIS that uses a feature extraction algorithm for person identification will tend to fail if it extracts spurious features from the noisy background area. So fingerprint image segmentation plays a crucial role in reliably separating ridge like part (foreground) from its background. In this paper, an algorithm for fingerprint image segmentation using GLCM textural feature is presented. Four block level GLCM features: Contrast, Correlation, Energy and Homogeneity are used for fingerprint segmentation. A linear classifier is trained for classifying per block of fingerprint image. The algorithm is tested on standard FVC2002 dataset. Experimental results show that the proposed segmentation method works well in noisy fingerprint images.


Fingerprint Segmentation GLCM features Logistic regression Morphological operations 


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Copyright information

© Springer Science+Business Media Singapore 2017

Authors and Affiliations

  1. 1.Karpagam UniversityCoimbatoreIndia
  2. 2.Karpagam UniversityCoimbatoreIndia

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