Minutiae Features Research Articles

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.

Distal-Interphalangeal-Crease-Based User Authentication System

Touchless-based fingerprint recognition technology is thought to be an alternative to touch-based systems to solve problems of hygienic, latent fingerprints, and maintenance. However, there are few studies about touchless fingerprint recognition systems due to the lack of a large database and the intrinsic drawback of low ridge-valley contrast of touchless fingerprint images. This paper proposes an end-to-end solution for user authentication systems based on touchless fingerprint images in which a multiview strategy is adopted to collect images and the robust fingerprint feature of touchless image is extracted for matching with high recognition accuracy. More specifically, a touchless multiview fingerprint capture device is designed to generate three views of raw images followed by preprocessing steps including region of interest (ROI) extraction and image correction. The distal interphalangeal crease (DIP)-based feature is then extracted and matched to recognize the human's identity in which part selection is introduced to improve matching efficiency. Experiments are conducted on two sessions of touchless multiview fingerprint image database with 541 fingers acquired about two weeks apart. An EER of ~ 1.7% can be achieved by using the proposed DIP-based feature, which is much better than touchless fingerprint recognition by using scale invariant feature transformation (SIFT) and minutiae features. The given fusion results show that it is effective to combine the DIP-based feature, minutiae, and SIFT feature for touchless fingerprint recognition systems. The EER is as low as ~ 0.5%.

A Novel Fingerprint Matching Algorithm Based on Compatible Multi-Area Alignment

Most minutiae-based matching algorithms consist of two phases, local match and global match. In the local phase, some corresponding pairs are obtained by comparing the affine-invariable features of minutiae. And then two images are aligned based on the candidate pairs. However, some spurious candidate pairs and the large nonlinear deformation in images lead to the failure in global match. In this paper, we proposed a novel minutiae-based matching scheme which insert a filtering step after the local match to discard the incompatible pairs and renovate the global match by dividing the whole image into small areas according to the location of the candidate pairs. Results on databases of FVC2004 validate our algorithm.

Operational bio‐hash to preserve privacy of fingerprint minutiae templates

The storage of fingerprints is an important issue as this biometric modality is more and more deployed for real applications. Considering minutiae templates as sensitive information, a key question concerns the secure and privacy management of this digital identity. Indeed, if an attacker obtains the minutiae template of a subject, he/she will be able to generate a fingerprint having the same characteristics. Instead of directly storing the minutiae templates, the authors propose in this study a new adaptation of BioHashing to generate a cancellable template in the context of un-ordered set of noisy minutiae features. To the authors knowledge, little interest has been paid in the literature to the question of protecting minutiae template by BioHashing until now. Using the FVC2002 benchmark database, they show the effectiveness of the proposed approach in term of privacy preservation. They show how the proposed method copes with irreversibility and diversity properties and therefore can be efficient in a realistic context.

Enhanced Thinning Based Finger Print Recognition

This paper is the implementation of fingerprint recognition system in which the matching is done using the Minutiae points. The methodology is the extracting & applying matching procedure on the Minutiae points between the sample fingerprint & fingerprint under question. The main functional blocks of this system follows steps of Image Thinning, Image Segmentation, Minutiae (feature) point Extraction, & Minutiae point Matching. The procedure of Enhanced Thinning included for the purpose of decreasing the size of the memory space used by the fingerprint image database.

Fingerprint Combination for Privacy Protection

We propose here a novel system for protecting fingerprint privacy by combining two different fingerprints into a new identity. In the enrollment, two fingerprints are captured from two different fingers. We extract the minutiae positions from one fingerprint, the orientation from the other fingerprint, and the reference points from both fingerprints. Based on this extracted information and our proposed coding strategies, a combined minutiae template is generated and stored in a database. In the authentication, the system requires two query fingerprints from the same two fingers which are used in the enrollment. A two-stage fingerprint matching process is proposed for matching the two query fingerprints against a combined minutiae template. By storing the combined minutiae template, the complete minutiae feature of a single fingerprint will not be compromised when the database is stolen. Furthermore, because of the similarity in topology, it is difficult for the attacker to distinguish a combined minutiae template from the original minutiae templates. With the help of an existing fingerprint reconstruction approach, we are able to convert the combined minutiae template into a real-look alike combined fingerprint. Thus, a new virtual identity is created for the two different fingerprints, which can be matched using minutiae-based fingerprint matching algorithms. The experimental results show that our system can achieve a very low error rate with FRR = 0.4% at FAR = 0.1%. Compared with the state-of-the-art technique, our work has the advantage in creating a better new virtual identity when the two different fingerprints are randomly chosen.

Incorporating Ridges with Minutiae for Improved Fingerprint verification

Next to DNA, fingerprint is the unique feature which identifies the individual. Distortions and skin deformations makes the fingerprint unreliable and it is difficult to match using minutiae alone. But when ridge features are incorporated with minutiae features (minutiae type, orientation and position) more topological information can be obtained. And also ridges are invariant to transformations such as rotation and translation[1]. Ridge based coordinate system is used to extract the ridge features such as ridge length, ridge count, ridge type and curvature direction in the skeletonized image. Breadth First Search is used to traverse the graph formed using the minutiae as the node and the ridge vector formed using the ridge features as the edge. The proposed ridge feature gives additional information for fingerprint matching with little increment in template size and can be used along with the existing minutiae features to increase the accuracy and robustness of fingerprint recognition systems.

A Robust Method for Fingerprint Recognition using Biometric Fusion

In this paper we will introduce a combined approach that uses the local and global features on the fingerprint. Minutiae features are extracted then a mesh of minutiae points relations will created. Then among the outputs of first stage two points used in the other stage as reference point and rotation handle. Matching process will take place after each stage then results made in both stages will be used to get the final answer. In this approach we used 10 fingerprints of persons to maximize the precision. Also we will use powerful pre-process tools to ensure that the input image is in the best condition for matching.

Fusion Fingerprint and Face Multi-Biometrics Recognition Based on D-S Evidence Theory

Single biometric feature has not meet people's needs. After analyzing fingerprints and face recognition technology, a fused theory is proposed which comprise fingerprints and face multi-biometrics features recognition based on D-S evidence theory. This article first analysis main part of the Face and Fingerprint Identification System, then gives a decision-making on integration in the face and fingerprint recognition method. In this paper we divide minutia features of fingerprint into certain and uncertain region which could make the performance of verification in certain region better than the original performance. By this fusion strategy the whole performance is improved.

Multifinger Feature Level Fusion Based Fingerprint Identification

(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 3, No. 11, 2012

An efficient strategy to detect latent fingermarks on metallic surfaces

The aim of this work is to use metal sputtering for the development of latent fingermarks on metallic surfaces by taking advantage of the prints' topography. In order to promote the preferential deposition onto fingerprints' ridges the deposition parameters should be optimized. After a previous selection, copper and gold thin films were deposited by magnetron sputtering onto stainless steel substrates where fingermarks were intentionally placed. After optimizing the deposition parameters, the influence of the fingermarks' age was studied. The quality of the developed fingermarks was evaluated visually and through optical and scanning electron microscopy. The morphology of the copper and gold thin films was examined by high resolution scanning electron microscopy. The preferential magnetron sputtering deposition of copper and gold thin films, 20-30 nm thick, allows latent fingermarks to be successfully developed. The gold films are more promising, especially for detecting non-fresh fingermarks and for conserving the developed marks. It was possible to detect the contours of the ridges and localize minutiae features in a one-month aged impression developed by gold deposition. These films present discontinuous surface and columnar cross-sections, while copper thin films have a featureless morphology.

Introducing a Semi‐Automatic Method to Simulate Large Numbers of Forensic Fingermarks for Research on Fingerprint Identification

Statistical research on fingerprint identification and the testing of automated fingerprint identification system (AFIS) performances require large numbers of forensic fingermarks. These fingermarks are rarely available. This study presents a semi-automatic method to create simulated fingermarks in large quantities that model minutiae features or images of forensic fingermarks. This method takes into account several aspects contributing to the variability of forensic fingermarks such as the number of minutiae, the finger region, and the elastic deformation of the skin. To investigate the applicability of the simulated fingermarks, fingermarks have been simulated with 5-12 minutiae originating from different finger regions for six fingers. An AFIS matching algorithm was used to obtain similarity scores for comparisons between the minutiae configurations of fingerprints and the minutiae configurations of simulated and forensic fingermarks. The results showed similar scores for both types of fingermarks suggesting that the simulated fingermarks are good substitutes for forensic fingermarks.

Fingerprint Matching Incorporating Ridge Features With Minutiae

This paper introduces a novel fingerprint matching algorithm using both ridge features and the conventional minutiae feature to increase the recognition performance against nonlinear deformation in fingerprints. The proposed ridge features are composed of four elements: ridge count, ridge length, ridge curvature direction, and ridge type. These ridge features have some advantages in that they can represent the topology information in entire ridge patterns existing between two minutiae and are not changed by nonlinear deformation of the finger. For extracting ridge features, we also define the ridge-based coordinate system in a skeletonized image. With the proposed ridge features and conventional minutiae features (minutiae type, orientation, and position), we propose a novel matching scheme using a breadth-first search to detect the matched minutiae pairs incrementally. Following that, the maximum score is computed and used as the final matching score of two fingerprints. Experiments were conducted for the FVC2002 and FVC2004 databases to compare the proposed method with the conventional minutiae-based method. The proposed method achieved higher matching scores. Thus, we conclude that the proposed ridge feature gives additional information for fingerprint matching with little increment in template size and can be used in conjunction with existing minutiae features to increase the accuracy and robustness of fingerprint recognition systems.

FINGERPRINT MATCHING BASED ON PORE CENTROIDS

In recent years there has been exponential growth in the use of biometrics for user authentication applications. Automated Fingerprint Identification systems have become popular tool in many security and law enforcement applications. Most of these systems rely on minutiae (ridge ending and bifurcation) features. With the advancement in sensor technology, high resolution fingerprint images (1000 dpi) provide micro level of features (pores) that have proven to be useful features for identification. In this paper, we propose a new strategy for fingerprint matching based on pores by reliably extracting the pore features The extraction of pores is done by Marker Controlled Watershed segmentation method and the centroids of each pore are considered as feature vectors for matching of two fingerprint images. Experimental results shows that the proposed method has better performance with lower false rates and higher accuracy.

Online Fingerprint Verification Algorithm and Distributed System

In this paper, a novel online fingerprint verification algorithm and distribution system is proposed. In the beginning, fingerprint acquisition, image preprocessing, and feature extraction are conducted on workstations. Then, the extracted feature is transmitted over the internet. Finally, fingerprint verification is processed on a server through web-based database query. For the fingerprint feature extraction, a template is imposed on the fingerprint image to calculate the type and direction of minutiae. A data structure of the feature set is designed in order to accurately match minutiae features between the testing fingerprint and the references in the database. An elastic structural feature matching algorithm is employed for feature verification. The proposed fingerprint matching algorithm is insensitive to fingerprint image distortion, scale, and rotation. Experimental results demonstrated that the matching algorithm is robust even on poor quality fingerprint images. Clients can remotely use ADO.NET on their workstations to verify the testing fingerprint and manipulate fingerprint feature database on the server through the internet. The proposed system performed well on benchmark fingerprint dataset.

Min Max Threshold Range (MMTR) based approach in palmprint authentication by sobel code method

Palmprint recognition is an effective biometric authentication method to automatically identify a person’s identity. Palmprint is rich in features like geometry features, line features, datum points, delta features and minutiae features. Several edge detection methods are available to extract line feature from the palmprint. In this paper, the hand image is pre-processed to get the desired Region of Interest (ROI)/palmprint. Multiscale Sobel Code operators of different orientations (0°, 45°, 90°, and 135°) are applied to the palmprint to extract Sobel-Palmprint features in different directions. The Sobel-Palmprint features extracted are stored in Sobel-Palmprint feature vector and matched using Hamming Distance similarity measurement method. In addition, a Min Max Threshold Range (MMTR) method is proposed that helps in increasing overall system accuracy by matching a person with multiple threshold values. In this technique, firstly the person is authenticated at global level using Reference threshold. Secondly, the person is authenticated at local level using range of Minimum and Maximum thresholds defined for a person. Generally, personal authentication is done using reference threshold but there are chances of false acceptance. So, by using the Minimum and Maximum Thresholds range of false accepted persons at personal level, a person is identified to be false accepted or genuinely accepted. MMTR is an effective technique to increase the accuracy of the palmprint authentication system by reducing the False Acceptance Rate (FAR). Experimental results indicate that the proposed method improves the False Acceptance Rate drastically.

A Fast Minutiae-Based Fingerprint Recognition System

The spectral minutiae representation is a method to represent a minutiae set as a fixed-length feature vector, which is invariant to translation, and in which rotation and scaling become translations, so that they can be easily compensated for. These characteristics enable the combination of fingerprint recognition systems with template protection schemes that require as an input a fixed-length feature vector. Based on the spectral minutiae features, this paper introduces two feature reduction algorithms: the Column Principal Component Analysis and the Line Discrete Fourier Transform feature reductions, which can efficiently compress the template size with a reduction rate of 94%. With reduced features, we can also achieve a fast minutiae-based matching algorithm. This paper presents the performance of the spectral minutiae fingerprint recognition system and shows a matching speed with 125 000 comparisons per second on a PC with Intel Pentium D processor 2.80 GHz and 1 GB of RAM. This fast operation renders our system suitable as a preselector for a large-scale fingerprint identification system, thus significantly reducing the time to perform matching, especially in systems operating at geographical level (e.g., police patrolling) or in complex critical environments (e.g., airports).

Finger-vein image recognition combining modified Hausdorff distance with minutiae feature matching

In this paper, we propose a novel method for finger-vein recognition. We extract the features of the vein patterns for recognition. Then, the minutiae features included bifurcation points and ending points are extracted from these vein patterns. These feature points are used as a geometric representation of the vein patterns shape. Finally, the modified Hausdorff distance algorithm is provided to evaluate the identification ability among all possible relative positions of the vein patterns shape. This algorithm has been widely used for comparing point sets or edge maps since it does not require point correspondence. Experimental results show that these minutiae feature points can be used to perform personal verification tasks as a geometric representation of the vein patterns shape. Furthermore, by this developed method, we can achieve robust image matching under different lighting conditions.

Finger-vein image recognition combining modified hausdorff distance with minutiae feature matching

Finger-vein image recognition combining modified hausdorff distance with minutiae feature matching

Extraction of minutiae and significant feature from fingerprint image

An improved algorithm for minutiae extraction was brought out.First,the set of original minutiae was directly extracted from thinned fingerprint images.Second,various noises in fingerprint images and their properties were analyzed and distributing regulation of pseudo minutiae was generalized.Last,combining with the information of local ridge direction,special algorithms were designed with respect to various noises to delete pseudo minutiae from original minutiae set.The remainders of original minutiae were viewed as intrinsic minutiae.According to the characteristics of fingerprint image,a new algorithm to extract the significant features was presented,by constructing three types of line feature in the complete image,and the line feature can be extracted out successfully from the sets of minutiae.