Fingerprint Reference-Point Detection

Abstract

<p/> <p>A robust fingerprint recognition algorithm should tolerate the rotation and translation of the fingerprint image. One popular solution is to consistently detect a unique reference point and compute a unique reference orientation for translational and rotational alignment. This paper develops an effective algorithm to locate a reference point and compute the corresponding reference orientation consistently and accurately for all types of fingerprints. To compute the reliable orientation field, an improved orientation smoothing method is proposed based on adaptive neighborhood. It shows better performance in filtering noise while maintaining the orientation localization than the conventional averaging method. The reference-point localization is based on multiscale analysis of the orientation consistency to search the local minimum. The unique reference orientation is computed based on the analysis of the orientation differences between the radial directions from the reference point, which are the directions of the radii emitted from the reference point with equivalent angle interval, and the local ridge orientations along these radii. Experimental results demonstrate that our proposed algorithm can consistently locate a unique reference point and compute the reference orientation with high accuracy for all types of fingerprints.</p

Orientation Field Estimation for Latent Fingerprint Enhancement

“…A large window can suppress the noise better while a small window can preserve the true orientation in high curvature region. Several authors have suggested using multi-resolution orientation fields to address this problem [9], [21], [30], [45]. However, when the noise is severe as in latents, smoothing techniques are not able to recover the true orientation field.…”

Fingerprint Recognition

“…Core point MATLAB code is available at (http://www.hackchina.com/en/cont/18456) where the idea of determining the reference point is taken from (Yang & Park, 2008), which is described as follows: The reference point is defined as "the point of the maximum curvature on the convex ridge (Liu et al, 2005)" which is usually located in the central area of fingerprint. The reliable detection of the position of a reference point can be accomplished by detecting the maximum curvature using complex filtering methods (Nilsson & Bigun, 2003).…”

Performance Improvement in Gradient based Algorithm for the Estimation of Fingerprint Orientation Fields

“…Ridge orientation is an important feature because the impact of it is affected to other processes like fingerprint enhancement, classification, segmentation and matching. The ridge orientation can be used in [4][5][6][7][8][9] image enhancement algorithms, singular points detection [5][ [10][11][12][16] and classification [13][14][15][16][17][18][19]. If accurate orientation estimation is not found then false recognition is generate.…”