作者:
Zhu, XiangrongHuang, DiIRIP
School of Computer Science and Engineering Beihang Univ. Beijing 100191 China
In recent years, hand dorsal vein has attracted increasing attentions of researchers in the domain of biometrics. this paper proposes a novel approach for hand dorsal vein identification, making use of boththe textur...
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Nowadays, the web has enabled an explosive growth of information sharing(there are currently over 4 billion pages covering most areas of human endeavor) so that the web has faced a new challenge of information overhea...
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ISBN:
(纸本)9780819490261
Nowadays, the web has enabled an explosive growth of information sharing(there are currently over 4 billion pages covering most areas of human endeavor) so that the web has faced a new challenge of information overhead. the challenge that is now before us is not only to help people locating relevant information precisely but also to access and aggregate a variety of information from different resources automatically. Current web document are in human-oriented formats and they are suitable for the presentation, but machines cannot understand the meaning of document. To address this issue, Berners-Lee proposed a concept of semantic web. With semantic web technology, web information can be understood and processed by machine. It provides new possibilities for automatic web information processing. A main problem of semantic web information retrieval is that when these is not enough knowledge to such information retrieval system, the system will return to a large of no sense result to uses due to a huge amount of information results. In this paper, we present the architecture of information based on semantic web. In addiction, our systems employ the inference Engine to check whether the query should pose to Keyword-based Search Engine or should pose to the Semantic Search Engine.
Finger vein patterns have recently been recognized as an effective biometric identifier and many related work can achieve satisfied results. However, these methods usually suppose the database is non-rotated or slight...
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Liveness detection is an indispensable guarantee for reliable face recognition, which has recently received enormous attention. In this paper we propose three scenic clues, which are non-rigid motion, face-background ...
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ISBN:
(纸本)9781467318723;9781467318716
Liveness detection is an indispensable guarantee for reliable face recognition, which has recently received enormous attention. In this paper we propose three scenic clues, which are non-rigid motion, face-background consistency and imaging banding effect, to conduct accurate and efficient face liveness detection. Non-rigid motion clue indicates the facial motions that a genuine face can exhibit such as blinking, and a low rank matrix decomposition based image alignment approach is designed to extract this non-rigid motion. Face-background consistency clue believes that the motion of face and background has high consistency for fake facial photos while low consistency for genuine faces, and this consistency can serve as an efficient liveness clue which is explored by GMM based motion detection method. Image banding effect reflects the imaging quality defects introduced in the fake face reproduction, which can be detected by wavelet decomposition. By fusing these three clues, we thoroughly explore sufficient clues for liveness detection. the proposed face liveness detection method achieves 100% accuracy on Idiap print-attack database and the best performance on self-collected face anti-spoofing database.
In statistical machine translation, word lattices are used to represent the ambiguities in the preprocessing of the source sentence, such as word segmentation for chinese or morphological analysis for German. Several ...
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As a non-invasive biometric method, face recognition in surveillance is a very challenging problem because of the concurrence of conditions, such as under the variable illumination with uncontrolled pose and movement ...
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ISBN:
(纸本)9783642331404
As a non-invasive biometric method, face recognition in surveillance is a very challenging problem because of the concurrence of conditions, such as under the variable illumination with uncontrolled pose and movement in low-resolution of subject. In this paper, we present a robust human face recognition system for surveillance. Unlike traditional recognition system which detect face region directly, we use a Cascade Head-Shoulder Detector (CHSD) and a trained human body model to find the face region in an image. To recognize human face, an efficient feature, Overlapping Local Phase Feature (OLPF), is proposed, which is robust to pose and blurring without adversely affecting discrimination performance. To describe the variations of faces, Adaptive Gaussian Mixture Model (AGMM) is proposed which can describe the distributions of the face images. Since AGMM does not need the topology of face, the proposed method is resistant to the face detection errors caused by wrong or no alignment. Experimental results demonstrate the robustness of our method on public dataset as well as real data from surveillance camera.
the phase-based image matching is effective for both iris and palm recognition tasks. Hence, we can expect that the approach may be useful for multimodal biometric system having palmprint and iris recognition capabili...
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ISBN:
(纸本)9780819490261
the phase-based image matching is effective for both iris and palm recognition tasks. Hence, we can expect that the approach may be useful for multimodal biometric system having palmprint and iris recognition capabilities. this paper investigates the fusion of palmprint and iris biometric at image level. A new image fusion algorithm named Baud limited image product (BLIP) especially for phase-based image matching is proposed. Based on this, a new multi-biometric fusion scheme at image level that combines BLIP and phase-based image matching is proposed. the effective region of iris and palm images are first extracted respectively, then they are fused into one small size image using BLIP, finally matched withthe template using phase-based image matching to get a score. the experimental results show that this new scheme can not only improve the system accuracy performance, but also reduce the memory size used to store the template and time consumed by the matching.
As a reliable personal identification method, iris recognition has been widely used for a large number of applications. Since a variety of iris devices produced by different vendors may be used for some large-scale ap...
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this paper proposes a simple but effective graph-based agglomerative algorithm, for clustering high-dimensional data. We explore the different roles of two fundamental concepts in graph theory, indegree and outdegree,...
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ISBN:
(纸本)9783642337178
this paper proposes a simple but effective graph-based agglomerative algorithm, for clustering high-dimensional data. We explore the different roles of two fundamental concepts in graph theory, indegree and outdegree, in the context of clustering. the average indegree reflects the density near a sample, and the average outdegree characterizes the local geometry around a sample. Based on such insights, we define the affinity measure of clusters via the product of average indegree and average outdegree. the product-based affinity makes our algorithm robust to noise. the algorithm has three main advantages: good performance, easy implementation, and high computational efficiency. We test the algorithm on two fundamental computervision problems: image clustering and object matching. Extensive experiments demonstrate that it outperforms the state-of-the-arts in both applications.
While locating the points used for obtaining the hand-shape features with high class separability, the stability of the point positions is easily influenced by the hand positions and the wearing decorations. this pape...
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