Combining multi-scale composite windows with hierarchical smoothing strategy for fingerprint orientation field computation

• Published in: Biomedical engineering online 2018-10, Vol.17 (1), p.136-136, Article 136
• Main Authors: Li, Haiyan, Wang, Tangyu, Tang, Yiying, Wu, Jun, Yu, Pengfei, Guo, Lei, Chen, Jianhua, Zhang, Yufeng
• Format: Article
• Language: English
• Subjects: Accuracy; Algorithms; Biometric recognition systems; Composite materials; Computation; Computational biology; Construction methods; Curvature; Dermatoglyphics; Deviation; Digitization; Experiments; Filtration; Fingerprint orientation field (OF); Fingerprint verification; Fingerprints; Gradient based method; Image Processing, Computer-Assisted - methods; Image quality; Image reconstruction; Information processing; Localization; Methods; Multiscale analysis; Noise; Noise sensitivity; Orientation; Pattern Recognition, Automated; Position (location); Smoothing; Strategy; Technology application; Three-digitized orientation-zone filtering; Two-digitized orientation-zone filtering; Weight; Weighted multi-scale composite window; Windows (computer programs)
• ISSN: 1475-925X; 1475-925X
• DOI: 10.1186/s12938-018-0559-4

Orientation field (OF) plays a very significant role in automatic fingerprint recognition systems. Many algorithms have been proposed for the estimation of fingerprints' OF but it is hard to solve the dilemma of correcting spurious ridge structure and avoiding singularity location deviation, especially for poor images. So far, the following drawbacks still need to be solved for OF construction methods for practical application: (1) How to adaptively choose block scales to resolve the contradiction between accuracy and anti-noise, since small scale is beneficial to accuracy but is sensitive to noise, while large scale is more resistant to noise, but the accuracy is deteriorated. (2) How to construct the genuine OF in the areas close-by singular points and to evade singularity location deviation? Current block based methods give spurious OF estimates in the area near singular points because these areas have large curvature thus the detected singular points deviate from the genuine localizations. When these singular points are used as the anchor for referencing minutiae, it makes the average error of matching or recognition even larger. Therefore, it is essentials to construct the genuine OF in the areas close-by singular points and to evade singularity deviation. To overcome the above-mentioned limitations, a novel method, combining a weighted multi-scale composite window (WMCM) with a hierarchical smoothing strategy has been proposed for the computation of fingerprint OF. This method mainly contains two procedures: the approximate OF estimation and the hierarchical OF smoothing. In the first procedure, a series of OFs are established under multiple scales of composite windows by using a gradient based method then a coarse OF is estimated using the weight of each scale determined by a squared gradient consistency. In the second procedure, the OF is first quantized into a two-digitized orientation zone and a two-orientation-zone filtering strategy is adapted to the OF blocks based on a filtering mask obtained after eliminating the isolated blocks. In the end a similar three-digitized orientation zone is performed to obtain an accurate and smooth OF. To validate the performance, the proposed method has been applied to OF computation using the FVC2004 databases and three experiments are designed. Experiment 1 aims to validate whether the weighted multi-scale composite window can balance the dilemma of accuracy and robustness more effectively than the previous w