International Journal of Biometrics (8 papers in press)
- Face recognition using a novel image representation scheme and multi-scale local features
by Qingchuan Tao, Zhiming Liu, George Bebis, Muhammad Hussain
Abstract: This paper presents a new method for improving face recognition performance under difficult conditions. The proposed method represents faces using multi-scale local features extracted from a novel representation of face images which employs color information. Specifically, past research on face recognition has shown that color information can improve recognition accuracy and robustness. Instead of using the primary colors, R, G, andrnB, a new image representation scheme is proposed which is derived from the YCrQ color space using Principal Component Analysis (PCA) followed by Fisher Linear Discriminant Analysis (FLDA). Multi-scale local features are used for face representation which are computed by extracting different resolution Local Binary Patterns (LBP) features from the new image representation and transforming the LBP features into the wavelet domain using Discrete Wavelet Transform (DWT) and Haar wavelets; we refer to this new type of features as LBP-DWT. To optimizeface representation, a variant of Nonparametric Discriminant Analysis (NDA), called Regularized Nonparametric Discriminant Analysis (RNDA) is introduced to extract the most discriminating features from LBP-DWT. The proposed methodology has been evaluated using two challenging face databases (i.e. FERET and Multi-PIE).We report promising experimental results showing that the proposed method outperforms two state-of-the-art methods, one based on Gabor features and the other based on Sparse Representation Classification (SRC). Further improvements are reported using score-level fusion.
Keywords: Face Recognition; Local Feature; Color Information; Nonparametric Discriminant Analysis
- Efficient Palmprint identification using novel symmetry filter and alignment refinement
by Hoang Thien Van
Abstract: This paper presents a robust algorithm for line orientation code based palmprint identification in which we propose a novel symmetry filter and an efficient alignment refinement technique. The main idea of the symmetry filter is to compute the approximate magnitude of the Gabor filter based on the modified finite Radon transform (MFRAT), the so-called GMFRAT filter. The advantages of GMFRAT filters are that (1) they are capable of quickly computing orientation codes, and (2) they remarkably reduce remarkably the sizes of these features. The alignment refinement technique, which uses local orientation patterns, is also proposed to solve the problem of rotations and translations caused by an imperfect preprocessing phase. Based on our alignment refinement, the matching algorithm is designed. Experimental results obtained using the public databases of the Hong Kong Polytechnic University and the Indian Institute of Technology Delhi demonstrate the effectiveness of the proposed method.
Keywords: Palmprint Recognition; Modified Finite Radon Transform; Gabor filter; GMFRAT filter; Alignment refinement
- Approach to Cryptographic Key Generation from Fingerprint Biometrics
by Subhas Barman, Debasis Samanta, Samiran Chattopadhyay
Abstract: To ensure security during data transmission, cryptography technique
is known to be a powerful approach. In general, cryptographic keys are large
and difficult to remember. To maintain the secrecy of cryptographic key, another
level of protection such as authentication step is required. As an alternative
to this, biometric can be considered along with cryptography called cryptobiometric
system (CBS), where either access of cryptographic key is controlled
with biometric or the key is generated from biometric features. This work related
to the latter issue in CBS. In such a system, protecting the privacy and security
of the biometric data is an important concern. Further, cryptography requires key
diversification which is not possible in case of biometric as it is inherent for a user. A way out, cancelable transformation of biometric prior to cryptography is
known. In this paper, we propose an approach to generate cryptographic key from
cancelable fingerprint templates (CT ) of sender and receiver for the enhancement
of network security. Both sender and receiver exchange their CT s with each other
and generate the cryptographic key at their ends using the CT s. In this approach,
CT ensures the privacy of the fingerprints and at the same time, it produces
revocable key for the application of symmetric cryptography. The between-person
variability of CT s guarantees the randomness which ensures that imposter users
are not able to generate a genuine CT to break the cryptographic key.
Keywords: Symmetric cryptography, cryptographic key generation, fingerprint,
cancelable template, network security, crypto-biometric system
- An Embedded System for Extracting Keystroke Patterns Using Pressure Sensors
by Christopher Leberknight
Abstract: The most popular biometric security technologies are fingerprint and iris recognition systems. Technologies that use these characteristics are extremely accurate because the patterns associated with an individual
Keywords: Biometrics;classification;keystroke analysis;pattern recognition;physical security;typing dynamics
- Research of Dual-Modal Decision Level Fusion for Fingerprint and Finger Vein Image
by Hui Ma
Abstract: The use of personal identity authentication systems with multi-modal biometrics has been proposed in order to increase the performance and robustness against environmental variation and fraudulent attacks. This paper presents a novel fingerprint and finger vein identity authentication system based on multi-route detection. Firstly, two classifiers are designed for fingerprint image and finger vein image respectively. Then extracted feature vectors from the first stage are then concatenated to make the third classifier. The final result is achieved by the fusion of the three classifiers recognition results at the decision level. Experimental results show that this algorithm not only overcomes the limitations of single-modal biometrics, but also effectively improves the recognition performance of the system.
Keywords: Biometrics; Concatenated classifier; Finger vein verification; Decision level Fusion
- Invariant face recognition using Zernike moments combined with feed forward neural network
by Vijayalakshmi G V Mahesh, Alex Noel Joseph Raj
Abstract: The paper proposes a face recognition system using Zernike moments (ZM) and feed forward neural network as a classifier. Magnitudes of the ZM, which are invariant to rotation, are used as feature vectors for efficient representation of the images. The experiment was conducted on the ORL and Texas 3D Face Recognition Database which has both color and range images. The recognition performance with measures like overall recognition accuracy, False acceptance rate, False rejection rate and True rejection rate was evaluated with Multilayer perceptron neural network, Radial basis function neural network and probabilistic neural network for variable lengths of the feature vector using confusion matrix. The simulation results indicates that the invariant ZM with neural network classifier was successful in recognizing the images constrained to different variations and illumination conditions. The overall classification accuracy of 99.7 % with MLPNN and 99.6% with MLPNN was achieved with range images and gray images from Texas 3D Face Recognition Database respectively. Furthermore 99.5% accuracy with RBFNN was achieved from ORL database.
Keywords: Zernike moments; feed forward neural network;rnMLPNN; RBFNN; PNN; face recognition; feature vector;recognition accuracy; invariant moments;confusion matrix; Accuracy; FAR; FRR; TRR;
Special Issue on: "Emerging Biometric Modalities,"
- Overview and Challenges of Palm Vein Biometric System
by Zarina Mohd Noh, Abdul Rahman Ramli, M. Iqbal Saripan, Marsyita Hanafi
Abstract: Palm vein biometric system is one of the biometric technologies that has grabbed the attention of scholarly researchers and industrial alike, due to its distinctive properties and hidden nature. Constant effort had been done in improving the palm vein biometric system performance through the design of its vein acquisition system and vein image analysis. This paper provides an overview of the underlying elements of a palm vein biometric system that summarizes the works done, and predicts the upcoming research focus in this area.
Keywords: palm vein pattern; biometric recognition; acquisition system; vein image analysis
- Multi-resolution elongated CS-LDP with Gabor Feature for Face Recognition
by Xi Chen, Fangyuan Hu, Zengli Liu, Qingsong Huang, Jiashu Zhang
Abstract: Center-symmetric local derivative pattern (CS-LDP) algorithm is proposed to describe the local second-order derivative feature of texture, However, CS-LDP can only describe second-order derivative feature of texture on four directions and lost some discriminant information on other directions. Addressing such problems, this paper proposed multi-resolution elongated CS-LDP (ME-CS-LDP) to solve such problem. By increasing the number of directions, which can be implemented by increasing the sampling points on the ellipse radius with interpolation, multi-resolution elongated CS-LDP can provide more discriminant information on more directions. Furthermore, our proposed multi-resolution elongated CS-LDP is defined in ellipse field to depict some important ellipse part of faces, like eyes and mouth. Gabor filter plus ME-CS-LDP/weighed ME-CS-LDP is used for face recognition in this paper. Experiments are carried out on the illumination subset of Yale B database，the subset of PIE illumination database and VALID face database. Experimental results have validated the effectiveness of the proposed method.
Keywords: Face recognition; Gabor filter; Multi-resolution elongated CS-LDP