Enhanced Ridge Direction for the Estimation of Fingerprint Orientation Fields

An accurate estimation of fingerprint orientation fields is an important step in the fingerprint classification process. Gradient-based approaches are often used  for estimating orientation fields of ridge structures but this method is susceptible to noise. Enhancement of ridge direction improves the structure of orientation fields and increases the number of correct features thereby conducing the overall performance of the classification process. In this paper, we propose an algorithm to improve orientation field structures using variance of gradient. That algorithm have two steps; firstly, estimation of fingerprint orientation fields using gradient-based method, and finally, enhancement of ridge direction using minimum variance of the cross center block direction. We have used standard fingerprint database NIST-DB14 for testing of proposed algorithm to verify the degree of efficiency of algorithm. The experiment results suggest that our enhanced algorithm achieves visibly better noise resistance with other methods

Fast algorithms for wavelet-based analysis of hyperspectral signatures

Hyperspectral sensors promise great improvements in the quality of information gathered for remote sensing applications. However, they also present a huge challenge to data storage and computing systems. Thus there is a great need for reliable compression schemes, as well as analysis tools that can exploit the hyperspectral data in a computationally efficient manner. It has been proposed that wavelet-based methods may be superior to currently used methods for the analysis of hyperspectral signatures. In this thesis, a wavelet-based method, as well as traditional analytical methods, was implemented and applied to hyperspectral images. The computational expense of the various methods are determined analytically and experimentally to show advantages of the wavelet-based methods. Various measures, including cross correlation, signal-to-noise ratios and Euclidean distance, are designed and implemented for comparing the differences that might exist between the outputs of the algorithms

Log-Gabor Orientation with Run-Length Code based Fingerprint Feature Extraction Approach

This paper aims to design and implement Log-Gabor filtering with Run-length Code based feature Extraction technique. Since minutiae extraction is an essential and core process of fingerprint Identification and Authentication systems, the minutiae features are enhanced in each orientation using Log-Gabor filter and features are extracted using the proposed method. Frequency domain is derived using FFT and they are enhanced by Log-Gabor filter for each orientation. In our method six orientations are considered; binarization, thinning are also followed. Fingerprint features are extracted using proposed method which possesses labeling and Run-length Coding technique. Our method is tested with the benchmark Databases and real time images and the results show the better performance and lower error rate

On-chip spectropolarimetry by fingerprinting with random surface arrays of nanoparticles

Optical metasurfaces revolutionized the approach to moulding the propagation of light by enabling simultaneous control of the light phase, momentum, amplitude and polarization. Thus, instantaneous spectropolarimetry became possible by conducting parallel intensity measurements of differently diffracted optical beams. Various implementations of this very important functionality have one feature in common - the determination of wavelength utilizes dispersion of the diffraction angle, requiring tracking the diffracted beams in space. Realization of on-chip spectropolarimetry calls thereby for conceptually different approaches. In this work, we demonstrate that random nanoparticle arrays on metal surfaces, enabling strong multiple scattering of surface plasmon polaritons (SPPs), produce upon illumination complicated SPP scattered patterns, whose angular spectra are uniquely determined by the polarization and wavelength of light, representing thereby spectropolarimetric fingerprints. Using um-sized circular arrays of randomly distributed {\mu}m-sized gold nanoparticles (density ~ 75 {\mu}m$^-$$^2$}) fabricated on gold films, we measure angular distributions of scattered SPP waves using the leakage radiation microscopy and find that the angular SPP spectra obtained for normally incident light beams different in wavelength and/or polarization are distinctly different. Our approach allows one to realize on-chip spectropolarimetry by fingerprinting using surface nanostructures fabricated with simple one-step electron-beam lithography.Comment: 22 pages, 5 figure

ARM7 based Smart ATM Access System

ARM7 Based Smart ATM System is designed to add more security to the ATM systems by using biometric, OTP and Accelerometer sensor. In our proposed system, Bankers will collect the customer’s fingerprints and mobile number while opening the account then only customers can access the ATM machine. The primary step of this project is to verify currently scanned finger print with the fingerprint which is registered in the bank. If it finds as a valid then ATM machine, will ask 4 digit pin which is fixed. If the 4 digit code matches with entered pin then system will automatically generates another different 4 digit code i.e. OTP. And that code will be message to the customer registered mobile number. Here customer has to enter this code again. After entering OTP, System will check whether entered code is valid or not. And if it is valid, the customer is allowed for further accessing. Also Accelerometer sensor is used in order to provide security for the ATM machine. DOI: 10.17762/ijritcc2321-8169.15059

Novel Feature Extraction Methodology with Evaluation in Artificial Neural Networks Based Fingerprint Recognition System

Fingerprint recognition is one of the most common biometric recognition systems that includes feature extraction and decision modules. In this work, these modules are achieved via artificial neural networks and image processing operations. The aim of the work is to define a new method that requires less computational load and storage capacity, can be an alternative to existing methods, has high fault tolerance, convenient for fraud measures, and is suitable for development. In order to extract the feature points called minutia points of each fingerprint sample, Multilayer Perceptron algorithm is used. Furthermore, the center of the fingerprint is also determined using an improved orientation map. The proposed method gives approximate position information of minutiae points with respect to the core point using a fairly simple, orientation map-based method that provides ease of operation, but with the use of artificial neurons with high fault tolerance, this method has been turned to an advantage. After feature extraction, General Regression Neural Network is used for identification. The system algorithm is evaluated in UPEK and FVC2000 database. The accuracies without rejection of bad images for the database are 95.57% and 91.38% for UPEK and FVC2000 respectively

Reconfigurable Intelligent Surfaces for Wireless Communications: Principles, Challenges, and Opportunities

Recently there has been a flurry of research on the use of reconfigurable intelligent surfaces (RIS) in wireless networks to create smart radio environments. In a smart radio environment, surfaces are capable of manipulating the propagation of incident electromagnetic waves in a programmable manner to actively alter the channel realization, which turns the wireless channel into a controllable system block that can be optimized to improve overall system performance. In this article, we provide a tutorial overview of reconfigurable intelligent surfaces (RIS) for wireless communications. We describe the working principles of reconfigurable intelligent surfaces (RIS) and elaborate on different candidate implementations using metasurfaces and reflectarrays. We discuss the channel models suitable for both implementations and examine the feasibility of obtaining accurate channel estimates. Furthermore, we discuss the aspects that differentiate RIS optimization from precoding for traditional MIMO arrays highlighting both the arising challenges and the potential opportunities associated with this emerging technology. Finally, we present numerical results to illustrate the power of an RIS in shaping the key properties of a MIMO channel.Comment: to appear in the IEEE Transactions on Cognitive Communications and Networking (TCCN