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A Review Paper on Multimodal Biometrics System using Fingerprint and Signature
Abstract
A biometric system is important to a pattern recognition system that operates by acquiring biometric data from an individual, extracting a feature set from the acquired data, and comparing this feature set against the template set in the database. Multimodal biometric systems are becoming more popular; Fingerprint recognition is the most popular physiological characteristic used to identify a person in biometric systems, because of feasibility, permanence, distinctiveness, reliability, accuracy, and acceptability Signature recognition is the most popular behavioral characteristic used in biometric systems. Thus, we believe that the combination of these two methods will have a reliable and accurate result. We propose a weighted fusion scheme, which transforms the scores into a common range, assigned weights and combines them, giving the final fused score.
Supplementary resource (1)
... The existing models for signature verification include polar domain, multi-stage classification, regression, support vector machine, k-nearest neighbor classifier, neural network, Zernike moments, circularity property, discrete wavelet transform, discrete random transform, and hidden Markov [10,[18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34]. The models have produced signature verification systems that exhibited various levels of performance, accuracy, and error, as well as suitability for the detection of skilled forgery. ...
... The study underscored the usefulness of some analysis parameters but failed to incorporate some efficiency-boosted classifiers. In [29], a simple signature recognition model for the detection of the shape or boundary features while guiding against interpolation loss was presented. The model uses random transform, Zernike moments, and a hidden Markov model for signature recognition and classification. ...
The human signature is a widely acceptable biometric characteristic that provides a very secure means for authorizing legal documents. However, signature-based authorization is characterized by problems of counterfeiting and forgery. Hence, the need for adequate verification and protection of signatures. On this note, this paper presents a signature similarity score model that is based on the transformation technique. The model comprises stages for pre-processing, feature extraction, and matching. The pre-processing stage performs Gabor and median filtering, normalization, rescaling, histogram equalization, binarization, and thinning. Gabor and Fourier’s transforms were used for feature extraction and Principal Component Analysis (PCA) for dimensionality reduction towards preventing information loss. The spatial frequency domain property of the input textures was extracted to form the texture features, while Fourier transform was applied to the texture features to obtain their rotation-invariant version. Finally, Euclidean distance-based feature analysis was carried out. Analysis of results from the experimental study of the model on the Netherlands Forensic Institute (NFI) standard signature dataset revealed that with the free or minimal noise level, the algorithm performed well. It was also established that each stage of the enhancement process is important for performance optimization. The comparison of experimental results with what was obtained for some similar and recent models showed an encouraging and superior performance level of the proposed model.
InMulti-modal biometrics has attracted strong interest in recent years and in future. This paper approaches to multi-modal biometrics based on biometric source, the type of sensing used, and the depth of collaborative interaction in the processing. This paper also attempts to identify some of the challenges and issues that confront research in multimodal biometrics.
The biometrics refers to technologies that measure and analyze human body characteristics, such as DNA, fingerprints, eye retinas and irises, voice patterns, facial patterns and hand measurements, for authentication purposes. Biometrics has been in the development for many years and with the recent advancements in technology has made some biometrics affordable and more reliable. Our goal is to show how DNA biometrics can improve the network security scheme of an organization. The process of biometrics will be broken down by its process and limitations, accessibility, accuracy, and use with applications. That's why DNA Biometric is essential to make for best recognition.
A biometric system is important to a pattern recognition system that operates by acquiring biometric data from an individual, extracting a feature set from the acquired data, and comparing this feature set against the template set in the database. Multimodal biometric systems are becoming more popular; Fingerprint recognition is the most popular physiological characteristic used to identify a person in biometric systems, because of feasibility, permanence, distinctiveness, reliability, accuracy, and acceptability Signature recognition is the most popular behavioral characteristic used in biometric systems. Thus, we believe that the combination of these two methods will have a reliable and accurate result. We propose a weighted fusion scheme, which transforms the scores into a common range, assigned weights and combines them, giving the final fused score.
Biometric recognition systems rely on a single biometric signature for authentication. While the advantage of using multiple sources of information for establishing the identity has been widely recognized, computational models for multimodal biometrics recognition have only recently received attention. We propose a multimodal sparse representation method, which represents the test data by a sparse linear combination of training data, while constraining the observations from different modalities of the test subject to share their sparse representations. Thus, we simultaneously take into account correlations as well as coupling information among biometric modalities. A multimodal quality measure is also proposed to weigh each modality as it gets fused. Furthermore, we also kernelize the algorithm to handle nonlinearity in data. The optimization problem is solved using an efficient alternative direction method. Various experiments show that the proposed method compares favorably with competing
The biometrics refers to technologies that measure and analyze human body characteristics, such as DNA, fingerprints, eye retinas and irises, voice patterns, facial patterns and hand measurements, for authentication purposes. Biometrics has been in the development for many years and with the recent advancements in technology has made some biometrics affordable and more reliable. Our goal is to show how DNA biometrics can improve the network security scheme of an organization. The process of biometrics will be broken down by its process and limitations, accessibility, accuracy, and use with applications. That's why DNA Biometric is essential to make for best recognition.
Finding the relationship between two coordinate systems using pairs of measurements of the coordinates of a number of points in both systems is a classic photogrammetric task. It finds applications in stereophotogrammetry and in robotics. I present here a closed-form solution to the least-squares problem for three or more points. Currently various empirical, graphical, and numerical iterative methods are in use. Derivation of the solution is simplified by use of unit quaternions to represent rotation. I emphasize a symmetry property that a solution to this problem ought to possess. The best translational offset is the difference between the centroid of the coordinates in one system and the rotated and scaled centroid of the coordinates in the other system. The best scale is equal to the ratio of the root-mean-square deviations of the coordinates in the two systems from their respective centroids. These exact results are to be preferred to approximate methods based on measurements of a few selected points. The unit quaternion representing the best rotation is the eigenvector associated with the most positive eigenvalue of a symmetric 4 × 4 matrix. The elements of this matrix are combinations of sums of products of corresponding coordinates of the points.
It has been observed that the reduced contact area offered by solid-state fingerprint sensors does not provide sufficient information (e.g., number of minutiae) for high accuracy user verification. Further, multiple impressions of the same finger acquired by these sensors, may have only a small region of overlap thereby degrading the matching performance of the verification system. To deal with this problem, we have developed a fingerprint mosaicking scheme that constructs a composite fingerprint template using multiple impressions. A composite template reduces storage, improves matching time and alleviates the problem of template selection. In the proposed algorithm, two impressions (templates) of a finger are initially aligned using the corresponding minutiae points. This alignment is used by a modified version of the well-known iterative closest point algorithm (ICP) to compute a transformation matrix that defines the spatial relationship between the two impressions. The resulting transformation matrix is used in two ways: (a) the two templates are stitched together to generate a composite image. Minutiae points are then detected in this composite image; (b) the minutia maps obtained from each of the individual impressions are integrated to create a larger minutia map. Our experiments show that a composite template improves the performance of the fingerprint matching system by 4%.
Performance rate of unimodal biometric system is often reduced due to physiological defects, user mode and the environment. Multibiometric systems seek to alleviate some of these drawbacks by providing multiple evidences of the same identity. In this paper, we develop a multimodal biometric system, FES, based on principal component analysis (PCA) and Fisher's linear discriminant (FLD) methods that will use face, ear and signature for identity identification and rank level fusion for consolidate the results obtained from these monomodal matchers. The ranks of individual matchers are combined using the Borda count method and the logistic regression method. The results indicate that fusing individual modalities improve the overall performance of the biometric system.
Offline Signature Verification using Euclidian Distance Closed-form solution of absoluteorientation using unit quaternions
- Ranjan Jana
Ranjan Jana et al, / (IJCSIT) International Journal of
Computer Science and Information Technologies, Vol. 5
(1), 2014, 707-710 Offline Signature Verification using
Euclidian Distance.
[5] Berthold K. P. Horn, " Closed-form solution of
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- Ranjan Jana
Ranjan Jana et al, / (IJCSIT) International Journal of
Computer Science and Information Technologies, Vol. 5
(1), 2014, 707-710 Offline Signature Verification using
Euclidian Distance.