Image-Based Approach to Fingerprint Acceptability Assessment

Introduction to Presentation Attack Detection in Fingerprint Biometrics

“…Other liveness detection approaches for fake fingerprint detection include: the combination of both perspiration and elasticity related features in fingerprint image sequences [44]; fingerprint-specific quality-related features [100,36]; the combination of the local ridge frequency with other multiresolution texture parameters [1]; techniques which, following the perspiration-related trend, analyze the skin sweat pores visible in high definition images [64,67]; the use of electric properties of the skin [65]; using several image processing tools for the analysis of the finger tip surface texture such as wavelets [69], or three very related works using gabor filters [73], ridgelets [74] and curvelets [72]; analyzing different characteristics of the Fourier spectrum of real and fake fingerprint images [29,45,46,54,62].…”

Fingerprint Smear Detection Based on Subband Feature Representation

“…Wu et al [15] proposed limited ring-wedge spectral measure to estimate the global fingerprint image features, and inhomogeneity with directional contrast to estimate local fingerprint image features. Uchida [16] computes a spatial changing pattern of gray level profile along with the frequency pattern of the images for feature extraction and classifies fingerprint images into two categories. Zhao et al [17] discussed the influence to fingerprint quality from the range of gray-scale, dry, wet to deflection.…”

Image Quality Measures for Fingerprint Image Enhancement

“…Fingerprint image quality is utilized to evaluate the system performance [1][2][3][4], assess enrollment acceptability [5] and improve the quality of databases, and evaluate the performances of fingerprint sensors. Uchida [5] described a method for fingerprint acceptability evaluation. It computes a spatial changing pattern of gray level profile along with the frequency pattern of the images.…”