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In this paper, we investigate a new method to analyze electrocardiogram (ECG) signal, extract the features, for the real time human identification using single lead human electrocardiogram. The proposed system extracts special parts of the ECG signal starting from the P wave, the QRS complex and ending with the T wave for that we used the multiresolution wavelet analysis. Different features are selected...
The theme of work presented in this paper is a novel Iris recognition technique using partial energies of transformed iris image. To generate transformed iris images, various transforms like Cosine, Walsh, Haar, Kekre, Hartley transforms and their wavelet transforms are applied on the iris images. Feature vectors are then generated from these transformed Iris images using the concept of energy compaction...
The strategy of extracting discriminant features from a face image is immensely important to accurate face recognition. This paper proposes a feature extraction algorithm based on wavelets and local binary patterns (LBPs). The proposed method decomposes a face image into multiple sub-bands of frequencies using wavelet transform. Each sub-band in the wavelet domain is divided into non-overlapping sub-regions...
This paper addresses biometric identification using large databases, in particular, iris databases. In such applications, it is critical to have low response time, while maintaining an acceptable recognition rate. Thus, the trade-off between speed and accuracy must be evaluated for processing and recognition parts of an identification system. In this paper, a graph-based framework for pattern recognition,...
Currently there is an increasing demand for human-recognition systems using Iris as a pattern for representing a person's identity. A typical Iris recognition system is composed of four steps: image acquisition, iris segmentation, feature extraction and matching. This paper focuses on the matching step. Particularly, it is proposed a new method of iris matching, the Novelty Filter, tailored to compare...
In this paper, we investigate the applicability of Electrocardiogram (ECG) signals for human identification. Wavelet Transform (WT) and Independent Component Analysis (ICA) methods are applied to extract morphological features that appear to offer excellent discrimination among subjects. The proposed method is aimed at the two-lead ECG configuration that is routinely used in long-term continuous monitoring...
This paper presents an efficient IrisCode classifier, built from phase features which uses AdaBoost for the selection of Gabor wavelets bandwidths. The final iris classifier consists of a weighted contribution of weak classifiers. As weak classifiers we use 3-split decision trees that identify a candidate based on the Levenshtein distance between phase vectors of the respective iris images. Our experiments...
It is shown that the application of wavelet packet analysis to the feature extraction part of an iris recognition system, is an interesting alternative to Gabor based methods. These methods use iris extraction and unwrapping. Wave atoms is a new transform which is half multi-scale and half multi-directional. This transform offers a better representation of images containing oscillatory patterns and...
The present article focuses on the classification of fingerprints. Our aim goal is to unify the process of fingerprint compression, classification and identification. The well known methods suited to these tasks are based on WSQ (Wavelet Scalar Quantization) for compression, Gabor filters for classification and minutiae matching for identification. We propose to use Block Ridgelet Transform (BRT)...
Iris recognition, as an emerging biometric recognition approach has become a major research topic with practical applications in recent years as it promises nearly perfect recognition rates. In this paper, a novel, efficient approach for iris recognition is presented. The goal is to develop a lifting (integer) wavelet based algorithm that enhances iris images, reduces noise to the maximum extent possible,...
Iris recognition recently became an active field of biometric security because of reliability and easy non-invasive acquisition of the data. The randomness and stability of the iris textures allow for a convenient application in personal authentication and identification. In a novel iris recognition method presented here, the iris features are extracted using the oriented separable wavelet transforms...
There has been increased concern about security during the past few years. Researchers are looking into developing new tools for security enhancement and this has brought biometrics into the limelight. The analysis of human gait as a biometric is relatively newer compared to finger prints, face or iris. This paper presents a new gait feature based on the wavelet analysis of the cyclic gait motion...
Authentication by biometric verification is becoming increasingly common in corporate, public security and other such systems. There is scads of work done in the area of offline palmprints like palmprint segmentation, crease extraction, special areas, feature matching etc. But to the best of our knowledge no work has been done yet to extract and identify the right hand of a person, given his/her left...
The challenges in biometrics research activities have expanded recently to include the maintenance of security and privacy of biometric templates beside the traditional work to improve accuracy, speed, and robustness. Revocable biometric templates and biometric cryptosystems have been developed as template protection measures. Revocability means that biometric templates could be revoked in the same...
The off line identification of the handwriting as of signature comes under the field of biometrics. The context of use is in particular in the banking and legal fields. Within this framework problems particularly of imitation and falsification are often met. This paper presents an approach of personal identification based on the fusion of two off line modalities: handwritten signature and handwriting...
Ear structure as a new class of biometrics can be used in many applications such as security systems. Ear structure is physiologically unique and stable, so ear recognition can be a good choice for a biometric security system. Even though, using ear biometric is not customary but it can be used with other biometrics like face or fingerprint simultaneously to increase the reliability of a biometric...
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