Biometric systems based on a single source of information suffer from limitations such as the lack of uniqueness, non-universality of the chosen biometric trait, noisy data and spoof attacks. Multibiometrics are relat...
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Biometric systems based on a single source of information suffer from limitations such as the lack of uniqueness, non-universality of the chosen biometric trait, noisy data and spoof attacks. Multibiometrics are relat...
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Biometric systems based on a single source of information suffer from limitations such as the lack of uniqueness, non-universality of the chosen biometric trait, noisy data and spoof attacks. Multibiometrics are relatively new systems that overcome those problems. These systems fuse information from multiple biometric sources in order to achieve better identification performance. In this paper, 2D and 3D palmprint are integrated in order to construct an efficient multibiometric identification system based on matching score level fusion. For that, the texture information is characterized by the rotation invariant VARiance measures (VAR) and compressed using the Principal Components Analysis (PCA). Subsequently, we use the Hidden Markov Model (HMM) for modeling the feature vector of each palmprint. Finally, Log-likelihood scores are used for palmprint evaluation. The proposed scheme is tested and evaluated using PolyU 2D-3D palmprint database of 250 users. Our experimental results show the effectiveness and reliability of the proposed system, which brings high identification accuracy rate.
Reliability and accuracy in personal identification system is a dominant concern to the security world. Biometric has gained much attention in this subject recently. Many types of personal identification systems have ...
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Reliability and accuracy in personal identification system is a dominant concern to the security world. Biometric has gained much attention in this subject recently. Many types of personal identification systems have been developed, and palmprint identification is one of the emerging technologies. This paper presents a novel biometric technique to automatic personal identification system using multispectral palmprint technology. In this method, each of spectrum images are aligned and then used to extract palmprint features using 1D log-Gabor filter. These features are then examined for their individual and combined performances. Finally, the hamming distance is used for matching of palmprint features. The experimental results showed that the proposed method achieve an excellent identification rate and provide more security.
In many large scale biometric-based recognition problems, knowledge of the limiting capabilities of underlying recognition systems is constrained by a variety of factors including a choice of a source encoding techniq...
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Randí et al. proposed a significant graphical representation for DNA sequences, which is very compact and avoids loss of information. In this paper, we build a fast algorithm for this graphical representation wit...
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The overall performance of any iris recognition system relies on the performance of its components, which are preprocessing, feature extraction and matching. Feature extraction is the important step of such recognitio...
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ISBN:
(纸本)9781424477159
The overall performance of any iris recognition system relies on the performance of its components, which are preprocessing, feature extraction and matching. Feature extraction is the important step of such recognition system, but it is strongly dependent on the pre-processing step that is consisting of localising and normalising the iris. In this paper, Independent Component Analysis (ICA), which is a recently developed statistical method for data analysis, is applied for extracting the features for iris region of interest that are statistically independent. Based on some mathematical criteria, the performance of ICA is evaluated by using two different subsets of CASIA-V3 iris image database. The obtained results are convincing and some future improved research works are subsequently envisaged.
Automatic personal identification using biometric information is playing a more and more important role in applications such as public security, access control, banking, etc. Palmprint identification is a subcategory ...
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Randić et al. proposed a significant graphical representation for DNA sequences, which is very compact and avoids loss of information. In this paper, we build a fast algorithm for this graphical representation with ti...
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Randić et al. proposed a significant graphical representation for DNA sequences, which is very compact and avoids loss of information. In this paper, we build a fast algorithm for this graphical representation with time complexity O(n 2 ), and find another important advantage in the representation: no degeneracy. Moreover, we propose a new method to do similarity analysis of DNA sequences based on the representation. The approach adopts four elements of covariance matrix as a descriptor, and is illustrated on the first exon of beta-globin genes from 11 different species.
The overall performance of any iris recognition system relies on the performance of its components, which are preprocessing, feature extraction and matching. Feature extraction is the important step of such recognitio...
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The overall performance of any iris recognition system relies on the performance of its components, which are preprocessing, feature extraction and matching. Feature extraction is the important step of such recognition system, but it is strongly dependent on the pre-processing step that is consisting of localising and normalising the iris. In this paper, Independent Component Analysis (ICA), which is a recently developed statistical method for data analysis, is applied for extracting the features for iris region of interest that are statistically independent. Based on some mathematical criteria, the performance of ICA is evaluated by using two different subsets of CASIA-V3 iris image database. The obtained results are convincing and some future improved research works are subsequently envisaged.
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