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Copyright of Ordnance Industry Automation is the property of Editorial Board for Ordnance Industry Automation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Fingerprint clusters recognize fingerprint images faster by minimizing the database search space. To this end, the Gaussian filter algorithm is first used to improve the image contrast and calculate the directional fields of the fingerprint, and then the K-means algorithm is used twice, the first time, it is used to classify the fingerprint in terms of the length and width of the fingerprint, and the age group it belongs to, the second time, it is used to classify the fingerprint in terms of to which pattern the direction of ridgelines belong, plain arch, tented arch, ulnar loop, central pocket loop, plain whorl, and double whorl. Due to the smaller search space in the database, good quality results and faster fingerprint recognition are produced. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Fingerprints are the oldest and most widely used form of biometric identification. Many researchers have addressed the fingerprint classification problem and significant progress has been made in designing automatic fingerprint identification systems (AFIS) over the past two decades. However, some design factors such as lack of reliable minutia extraction algorithms, difficulty in quantitatively defining a reliable match between fingerprint images, poor image acquisition, low contrast images create bottlenecks in achieving the desired performance. Noticeable among them is the fact that digitally acquired fingerprint images are rarely of perfect quality to be used directly with AFIS; one important step is fingerprint enhancement. Conventional fingerprint enhancement methods, such as Gabor and anisotropic filters, do fill the holes and gaps in ridge lines but lack the necessary capability to tackle scar lines. For scar lines, an explicit filling process is proposed that is a mix of Fourier and spatial domain strategies. The proposed method is to make use of the Fourier domain directional field to trace an appropriate candidate for the scar pixels to be replaced with. The necessary components of the process are locating scars, estimating directional field, and the filling strategy. This process can act as front-end to the subsequent Gabor and anisotropic diffusion filtering. The simulation results for synthetic, as well as real fingerprints, show improved performance regarding better extraction of genuine minutia points. [ABSTRACT FROM AUTHOR]

Algorithms for interpreting (decoding) of interferograms plotted by the finite-element method are considered. Three directional field-building methods are used in them: the (i) complex averaging method, (ii) the projection-dispersion method, and (iii) the spectral method. The efficiency of the algorithms is checked on simulated and real interferograms. [ABSTRACT FROM AUTHOR]

Abstract: The singular points of fingerprints, namely core and delta, play an important role in fingerprint recognition and classification systems. Several traditional methods have been proposed; however, these methods cannot achieve the reliable and accurate detection of poor-quality fingerprints. In this paper, an algorithm is proposed which combines improved Poincaré index and multi-resolution analysis to detect singular points. Conventional Poincaré index method is improved on the basis of the Zero-pole Model analysis to detect singular points with different resolutions. A model is presented to extract the multi-resolution information of the fingerprint pattern; this model divides fingerprint image into nonoverlapping blocks corresponding to different block sizes on the basis of wavelet functions to compute multiple resolution directional fields, and block position shifting is performed on these resolution levels to capture the features of the ridge direction patterns, where the corresponding shifting intervals are based on Sampling theorem. The relationship of singularities detected by improved Poincaré index in different resolution directional fields is used to confirm singular points accurately and reliably. The combination of local and global information makes our algorithm more robust to noise than methods that use local information only, and the existence of this algorithm increases the insight into the nature of singular points extraction. The accuracy and reliability of the method are demonstrated by experiment on database NIST-4, public fingerprint databases FVC02 DB1 and DB2. [Copyright &y& Elsevier]

A method is proposed for constructing noise-resistant mask differentiating filters minimizing systematic errors in estimating directional fields by a gradient algorithm. A comparative analysis of the accuracy of gradient algorithms was performed by computer modeling It is shown that a decrease in the systematic error leads to a considerable increase in the accuracy of directional field estimation [ABSTRACT FROM AUTHOR]

A new device designed by the senior author of the current paper was examined and tested in the Materials Research Laboratory of The Pennsylvania State University. The device consists of an unconventionally driven magnetron whose directional output is conditioned by filters and a tailored horn antenna. Although the origin of the radiation is an ordinary 600 W magnetron, the modified radiation is not contained by either a Faraday cage or by microwave shielding. It interrupts the operation of electronic devices, shutting them off without apparent harm to the circuitry. The radiation was observed to pass through or circumvent a one inch block of aluminium. Lastly, it unexpectedly attenuated in the building ventilation ducts which were completely outside of the directional field, resulting in the heating of and off-gassing from sealant in the duct flanges. [ABSTRACT FROM AUTHOR]

A method for constructing fast projection-variance algorithms based on convolution algorithms for calculating variances of Radon projections is proposed. It is shown that the use of bilinear interpolation of the convolution kernel and parabolic interpolation of quantized estimates of directional fields increases the accuracy of the algorithms by more than a factor of 2. Two methods for constructing directional fields on the basis of Radon projections are considered and compared. Examples are given showing the computational efficiency, accuracy, and noise resistance of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a new fingerprint singular point detection method that is type-distinguishable and applicable to various fingerprint images regardless of their resolutions. The proposed method detects singular points by analyzing the shapes of the local directional fields of a fingerprint image. Using the predefined rules, all types of singular points (upper core, lower core, and delta points) can be extracted accurately and delineated in terms of the type of singular points. In case of arch-type fingerprints there exists no singular point, but reference points for arch-type fingerprints are required to be detected for registration. Therefore, we propose a new reference point detection method for arch-type fingerprints as well. The result of the experiments on the two public databases (FVC2000 2a, FVC2002 2a) with different resolutions demonstrates that the proposed method has high accuracy in locating each types of singular points and detecting the reference points of arch-type fingerprints without regard to their image resolutions. [Copyright &y& Elsevier]

As a global feature of fingerprints, the thinning of ridges, extraction of minutiae and computation of orientation field are very important for automatic fingerprint recognition. Many algorithms have been proposed for their computation and estimation, but their results are unsatisfactory, especially for poor quality fingerprint images. In this paper, a robust wavelet-based method to create thinned ridge map of fingerprint for automatic recognition is proposed. Properties of modulus minima based on the spline wavelet function are substantially investigated. Desirable characteristics show that this method is suitable to describe the skeleton of the ridge of the fingerprint image. A multi-scale thinning algorithm based on the modulus minima of wavelet transform is presented. The proposed algorithm is able to improve the skeleton representation of the ridge of the fingerprint without side-effects and limitations of the existing methods. The thinned ridge map can facilitate the extraction of the minutiae for matching in fingerprint recognition. Experiments have been conducted to validate the effectiveness and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

We propose a fast fingerprint matching methodology based on localizing the matching regions in captured fingerprint images. The determination of the locations of such regions relies on the accurate detection of reference points in the images together with a priori knowledge of the complete fingerprint obtained during the fingerprint enrollment procedure. The relationship between authentication reliability and region size is studied experimentally. Results show that sufficiently accurate fingerprint matching can be achieved using very small bitmaps, making it possible to implement very fast fingerprint authentication systems using the relatively slow embedding processors. [ABSTRACT FROM AUTHOR]