Automatic Fingerprint Identification Research Articles

Analysis of the Influence of Non-Directional Algorithms on Fingerprint Image Enhancement

Fingerprint image enhancement is of key importance for the efficiency of the automated fingerprint identification system. Before we can enhance a fingerprint image with contextual filters, we need to enhance fingerprint image contrast and readability with non-directional filters. This article provides an analysis of the influence of non-directional image enhancement techniques in the fingerprint image pre-processing step. To perform the analysis we used global normalization algorithm, local normalization algorithm, Wiener filter, histogram equalization algorithm and median filter. To evaluate the equal error rate in the experiments, done on a public database FVC_2004, we used Gabor filter and a state-of-the-art two-stage algorithm. DOI: http://dx.doi.org/10.5755/j01.eee.20.6.7277

Fingerprint Identification System: Non-zero Effort Attacks for Immigration Control

A growing security issue today in Nigeria is the increased occurrence of identity fraud. Research shows that perpetrators of this act are foreigners who enter the country without any document and are employed as security officers, thereby posing security treats to lives and properties. It has been noted that these foreigners device a means of beating security devices put in place at the border. The Nigerian Immigration uses Automated Fingerprint identification system (AFIS) which is minutiae base and it’s less noise tolerant unlike the correlation base approach. This paper therefore proposes a novel fingerprinting method that can help identify identity fraud. The method combines two approaches namely minutiae and correlation approaches, the idea is to see how the shortcomings of one is complemented by the other and the two approaches processes extraction and matching so as to get good and reliable images. Each of the approaches computes the matching score and the mean of the two resulting scores is taken. The mean is compared with the established threshold such that the system provides response by indicating whether the verification is successful or not. It follows that the adoption of this new method by organizations like the Nigerian Immigration Service will drastically reduce, if not totally eradicate, the level of insecurity in the country.

Fingerprint singular points extraction based on orientation tensor field and Laurent series

Singular point (SP) extraction is a key component in automatic fingerprint identification system (AFIS). A new method was proposed for fingerprint singular points extraction, based on orientation tensor field and Laurent series. First, fingerprint orientation flow field was obtained, using the gradient of fingerprint image. With these gradients, fingerprint orientation tensor field was calculated. Then, candidate SPs were detected by the cross-correlation energy in multi-scale Gaussian space. The energy was calculated between fingerprint orientation tensor field and Laurent polynomial model. As a global descriptor, the Laurent polynomial coefficients were allowed for rotational invariance. Furthermore, a support vector machine (SVM) classifier was trained to remove spurious SPs, using cross-correlation coefficient as a feature vector. Finally, experiments were performed on Singular Point Detection Competition 2010 (SPD2010) database. Compared to the winner algorithm of SPD2010 which has best accuracy of 31.90%, the accuracy of proposed algorithm is 45.34%. The results show that the proposed method outperforms the state-of-the-art detection algorithms by large margin, and the detection is invariant to rotational transformations.

Fingerprint Classification Method based on J-divergence Entropy and SVM

Fingerprint classification is one of the key technologies in Automatic Fingerp rint Identification System (AFIS). However, the performance of most recent fingerprint classification methods is lo w when the quality of the fingerprint image was low. To overcome this problem, a novel method based on j-divergence entropy and SVM (Support Vector Machine) classifier is proposed in this paper. Firstly, our method transforms the fingerprint images from spatial doma in to frequency domain and constructs the directional images according to frequency spectrum energy. Secondly, eigenvector around the core point is extracted. Thirdly, the dimension of eigenvector is reduced by j-divergence entropy. At last, the input image is classified by SVM classifier. Experimental results on NIST-4 database show the validity of our method, and the classification accuracy reaches 9 4.7% for four-class classification and 91.5% for five-class classification with zero rejection rate.

A Framework for Reproducible Latent Fingerprint Enhancements.

Photoshop processing1 of latent fingerprints is the preferred methodology among law enforcement forensic experts, but that appproach is not fully reproducible and may lead to questionable enhancements. Alternative, independent, fully reproducible enhancements, using IDL Histogram Equalization and IDL Adaptive Histogram Equalization, can produce better-defined ridge structures, along with considerable background information. Applying a systematic slow motion smoothing procedure to such IDL enhancements, based on the rapid FFT solution of a Lévy stable fractional diffusion equation, can attenuate background detail while preserving ridge information. The resulting smoothed latent print enhancements are comparable to, but distinct from, forensic Photoshop images suitable for input into automated fingerprint identification systems, (AFIS). In addition, this progressive smoothing procedure can be reexamined by displaying the suite of progressively smoother IDL images. That suite can be stored, providing an audit trail that allows monitoring for possible loss of useful information, in transit to the user-selected optimal image. Such independent and fully reproducible enhancements provide a valuable frame of reference that may be helpful in informing, complementing, and possibly validating the forensic Photoshop methodology.

Extraction of Direction Features in Fingerprint Image

This paper mainly discusses on the extraction method of an important feature----direction image in automatic fingerprint identification system, Point and block direction are respectively calculated of fingerprint image after preprocessing. The results in the paper could provide the basis for studying matching characteristics of subsequent fingerprint. All works achieved are performed in the VC environment.

A novel approach on cluster-based indexing technique for level-1 and level-2 fingerprint features

In recent years, automated fingerprint identification system (AFIS) plays a predominant role in personal authentication and verification. Fingerprint indexing is still a challenging issue in an AFIS as the size of database nowadays is huge. This paper proposes a cluster-based indexing on fingerprint features. The feature extraction of a fingerprint image is at three levels: level-1, level-2 and level-3. Fingerprint indexing is broadly classified as correlation-based matching, minutiae-based matching and non-minutiae-based matching. The fingerprint database is clustered using k-means algorithm. The fingerprint indexing methodology projected in this work is based on a combination of level-1 and level-2 features.

A Novel System of Fingerprint Recognition Approach for Immigration Control

Insecurity is a pressing and important issue that needs urgent attention in Nigeria. The dramatic increase in worldwide flow of people, goods, and ideas has created a new group of threats. These are global organized crimes such as smuggling, trafficking, terrorism; cross-border crimes, illegal migration, amongst others. It has been noted that these foreigners device a means of beating security devices put in place at the border. The Nigerian Immigration uses Automated Fingerprint identification system (AFIS) minutiae base, which is the most popular and extensively used method for fingerprint identification. It show poor performance for real time authentication and it has less noise tolerant unlike the correlation base approach. The authors therefore proposes an hybrid fingerprinting method that combines two approaches namely minutiae and correlation methods that can help identify identity fraud. The sole idea behind this is that one technique makes up for the deficiency of the other by so doing we obtain a reliable and efficient result and provide a more secured environment where immigrants will not be able to beat the system with their fraudulent tactics or acts as currently experienced. Java programming language is used because of its platform independence, scalability, easy integration, implementation and upgrade.

Standardized Biometric Templates in Indian Scenario: Interoperability Issues and Solutions

The compelling need for establishing the identity of a person is becoming critical in our vastly interconnected society. Biometrics is beginning to gain wide acceptance as a legitimate method for determining an individual’s identity in India. Minutiae features extracted from fingerprint images are widely used for automated fingerprint recognition. The conformance of minutiae templates to standardized data interchange formats and the interoperability of minutiae extraction and comparison subsystems from multiple suppliers are important to prevent proprietary lock-in. Further, just by achieving vendor-neutral fingerprint biometric templates, doesn’t guarantee seamless integration and exchange of information amongst different government agencies in India, viz., Aadhaar-enabled citizen services/applications, Seafarers' Identity Cards (ILO-SID) of DG Shipping, State-police AFISs (Automated Fingerprint Identification Systems) etc. One of the key reasons to this interoperability issue is the existence of multiple international standards for generation of minutiae-based fingerprint templates, which are primarily not interoperable. This paper focuses on conformance and interoperability issues that are likely to arise at the time of integration of such virtually isolated govt. agencies, specifically, in applications like, conducting nation-wide criminal background checks, de-duplication of data, etc. The paper further proposes viable solutions to address these issues.

Performance Improvisation on 3D Converted 2D Unraveled Fingerprint

Fingerprint authentication system has been widely emerged in authentication purpose in public as well as in private organizations. Normally fingerprint image processing is done in form of acquiring 2-D images, by using Automatic Fingerprint Identification System. The captured 2D texture will contain distortions. While comparing the enrolled distorted image from database with that of identification image, the results will be leads to false acceptance rate and false rejection rate. This paper deals with capturing of 3D fingerprint image and processed to attain improvisation in the resultant fingerprint image. The proposed scan system is based on real-time capturing by using low 3D sensor and with structured light illumination. This results in the generation of detailed in-depth ridge information and the texture of the finger in the form of 3D image. Thus generated 3D image is then converted to unraveled equal 2D images by using the proposed best fit sphere algorithm. The NIST matching software is employed to analyze and evaluate the image quality. The comparison is made between the unraveled converted 2D image and with its 2D ink-rolled data. The NIST matching software is then applied for 2D unraveled equivalent fingerprint images and results are analyzed. As a result, the fingerprints quality is improvised.

Fingerprint quality assessment based on wave atoms transform

Fingerprint image quality is of great importance for an automatic fingerprint identification system (AFIS), and affects its performance. In this paper, a new fingerprint image quality measure based on wave atoms transform is proposed. Indeed, fingerprint features are extracted by exploiting wave atoms multi-scale and multi-directional properties. Hence, for good quality block, the singularities are concentrated in a same directional subbands. In the opposite, for poor quality, the singularities are scattered over several directional subbands. In order to evaluate the performance of the algorithm, FVC (2002) databases have been considered. The results show that this method has a serious potential in fingerprint quality evaluation and will improve the performance and effectiveness of AFIS.

Evidence evaluation in fingerprint comparison and automated fingerprint identification systems—Modeling between finger variability

In the context of the investigation of the use of automated fingerprint identification systems (AFIS) for the evaluation of fingerprint evidence, the current study presents investigations into the variability of scores from an AFIS system when fingermarks from a known donor are compared to fingerprints that are not from the same source. The ultimate goal is to propose a model, based on likelihood ratios, which allows the evaluation of mark-to-print comparisons. In particular, this model, through its use of AFIS technology, benefits from the possibility of using a large amount of data, as well as from an already built-in proximity measure, the AFIS score. More precisely, the numerator of the LR is obtained from scores issued from comparisons between impressions from the same source and showing the same minutia configuration. The denominator of the LR is obtained by extracting scores from comparisons of the questioned mark with a database of non-matching sources. This paper focuses solely on the assignment of the denominator of the LR. We refer to it by the generic term of between-finger variability. The issues addressed in this paper in relation to between-finger variability are the required sample size, the influence of the finger number and general pattern, as well as that of the number of minutiae included and their configuration on a given finger. Results show that reliable estimation of between-finger variability is feasible with 10,000 scores. These scores should come from the appropriate finger number/general pattern combination as defined by the mark. Furthermore, strategies of obtaining between-finger variability when these elements cannot be conclusively seen on the mark (and its position with respect to other marks for finger number) have been presented. These results immediately allow case-by-case estimation of the between-finger variability in an operational setting.

Quality improvement of fingerprints of decayed corpses by local thanatopractical processing (Thanatoprint).

Thanatopractical processing allows morphological reconstruction of even advanced decayed bodies. By extracting fluids from the body’s tissue antemortem tenseness and volume can be restored. If bodies are partly subject to thanatopractical processing in the hand region (“Thanatoprint”), fingerprints of high quality can be gathered even in cases of advanced decay. Without this treatment fingerprinting can be extremely difficult, if not impossible. Thanatopractical processing could be applied successfully in cases of partial to subtotal detachment of the epidermis as well. In an interdisciplinary study 400 fingerprints of bodies in various states of decay were examined after application of Thanatoprint. In 76.75% fingerprints were applicable for data entry into AFIS (Automated Fingerprint Identification System); another 11.00% of the fingerprints could be used for the process of non-elimination. Further advantages of the method are low invasivity while maintaining the integrity of the corpse, less time- and material requirement as well as its long-lasting effect.

Fingermark Evidence Evaluation Based on Automated Fingerprint Identification System Matching Scores: The Effect of Different Types of Conditioning on Likelihood Ratios

In recent studies, the evidential value of the similarity of minutiae configurations of fingermarks and fingerprints, for example expressed by automated fingerprint identification systems (AFIS), is determined by likelihood ratios (LRs). The paper explores whether there is an effect on LRs if conditioning takes place on specified fingers, fingerprints, or fingermarks under competing hypotheses: In addition, an approach is explored where conditioning is asymmetric. Comparisons between fingerprints and simulated fingermarks with eight minutiae are performed to produce similarity score distributions for each type of conditioning, given a fixed AFIS matching algorithm. Both similarity scores and LRs are significantly different if the conditioning changes. Given a common-source scenario, "LRs" resulting from asymmetric conditioning are on average higher. The difference may reach a factor of 2000. As conditioning on a suspect's finger(print) is labor-intensive and requires a cooperating suspect, it is recommended to just condition on the number of minutiae in the fingermark.

Gender Specification Using Touch less Fingerprint Recognition

Fingerprint recognition or fingerprint authentication refers to the automated method of verifying a match between two human fingerprints.Fingerprints are one of many forms of biometrics used to identify individuals and verify their identity. This article touches on two major classes of algorithms (minutia and pattern) and four sensor designs (optical, ultrasonic, passive capacitance, and active capacitance).Most of the current security and attendance systems are shifting towards automated biometric systems, the most popular biometrics being fingerprints. In Automated Fingerprint Identification Systems (AFIS), the fingerprint of an individual needs to be identified with that stored in the database. In this is a method which deals with fingerprint identification in the transform domain is considered and the main focus is on the reduction of the processing time. First, the mean of rows (or columns) of the fingerprint image is computed, this converts a two dimensional image signal into one dimension. The one dimensional Walsh transform of the row (or column) vector is generated and is distributed in a complex plane which is subjected to sectorization to generate the feature vector.The feature vector of a given test image is compared to those present in the database. The scores from row and column transform methods are fused using OR and MAX functions. The results with accuracy of more than 73% (for 16 sectors) and high computational speed show that the method can be used in fingerprint identification in application with requirements of less processing time.

Survey on Fingerprint Enhancement Techniques

In the field of security, many Automatic Fingerprint Identification System (AFIS) have been developed. One of the indices for evaluating the security of such system is the quality of the fingerprint image and the efficiency of the enhancement algorithm used. The main aim of the paper is to present a survey on traditional and classical fingerprint image enhancement techniques. The performance of the enhancement algorithms are evaluated on the basis of PSNR and MSE values. Based on the above measures, the most efficient enhancement algorithm is chosen.

Fingerprint Image Segmentation Using Haar Wavelet and Self Organizing Map

Fingerprint image segmentation is one of the important preprocessing steps in Automatic Fingerprint Identification Systems (AFIS). Segmentation separates image background from image foreground, removing unnecessary information from the image. This paper proposes a new fingerprint segmentation method using Haar wavelet and Kohonen’s Self Organizing Map (SOM). Fingerprint image was decomposed using 2D Haar wavelet in two levels. To generate features vectors, the decomposed image was divided into nonoverlapping blocks of 2x2 pixels and converted into four elements vectors. These vectors were then fed into SOM network that grouped them into foreground and background clusters. Finally, blocks in the background area were removed based on indexes of blocks in the background cluster. From the research that has been carried out, we conclude that the proposed method is effective to segment background from fingerprint images.

A Challenge to Analyze and Detect Altered Human Fingerprints

The deployment of Automated Fingerprint Identification Systems (AFIS) in law enforcement and border control applications has escalated the need for ensuring that these systems are not compromised. Several problems related to fingerprint system security have been investigated carefully;, the problem of fingerprint alteration has received very scarce attention (1). Fingerprint alteration refers to the deliberate alteration of the fingerprint pattern by a person for masking his/her identity. Several cases of fingerprint alteration have been reported previously. The main contributions of this paper is: 1) Analysis of the altered fingerprints 2) classifying the alterations into three major categories: Obliteration, distortion and imitation and suggesting possible countermeasures 3) Demonstrating by using an example of database, where based on matching score the person of interest is branded as guilty or not and then based on decrease in value of matching score(4)(1) if below threshold value we can declare that the fingerprint is altered or not then combine fingerprint Image with person's UID(Unique Identity) comparing with that fingerprint with existing fingerprints showing if there is any match in the form of percentage and display his/her details with criminal record, 4) developing the above system by a technique to automatically detect altered fingerprints based on segmentation using Morphological operations, minutia marking with special considering the triple branch counting(11), minutia unification by decomposing a branch into three terminations(11)(12), and matching in the unified x-y coordinate system orientation estimation(13), minutiae matching after a two-step transformation.

Research on Cogent Automatic Fingerprint Identification System

Cogent Automatic Fingerprint Identification System (CAFIS) was researched by Cogent Co. Ltd. This system filtrated and matched fingerprints feathers automatically by computer to search for similar fingerprints, which are identified by specialists finally. It can provide help for criminal cases. About CAFIS, this paper introduces the principle, fingerprint identification process and the system workflow. Then, it researches five functions modules; they are image acquisition, screening, feathers matching, scoring and sorting; and introduce the algorithm of feather matching briefly. Experimental results show that it has many advantages, such as the big capacity of database, quick matching speed, high accuracy, etc.

Significance of 2006 Head Counts and House Census to Nigerian Sustainable Development

Population census, Limitations, Sustainable development, Virtues, Nigeria The 2006 population censu was scheduled, planned an d executed. The objective of this paper is to highlight the uniqueness and credi ble attributes of the exercise: and to make recommendations for subsequent census ethe country. The state commisioners were interviewed. NPC (National Population Commision) websites was visited and documents from the NPC of fice were perused. Literatures on National Population Commision were aread and used. The structure, system and organization can be compared to thatof developed countries. The organisation now use new and improve d technology. The activities of the organisation are more reliable as enumeratio n areas were demarcated to scales. AFIS (Automated Fingerprint Identification System) were implored and Geographic Information System was intended to be us ed to store the results. Suffice it to say that despite all efforts made by all organs of Government to create awareness and plan logistics, some challenges were still encountered. Nevertheless, there were also some positive respons es as it threw more light on the number, quality, type and design of houses in v arious communities. All organs of the governments were engaged. From planning to e xecution, adequate awareness and preparation were made to avoid the us ual riddles that characterized the previous exercises. The total pop ulation is 140, 003,542 unevenly distributed on the territory.