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International Conference on Pattern Recognition

作者： Yuhang Zhao Zhaoxiang Zhang Yunhong Wang Jianyun Liu Intelligent Recognition and Image Processing Lab Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University

ISBN: (纸本)9781467322164

Short message service (SMS) is now an indispensable way of social communication. However the mobile spam is getting increasingly serious, troubling users' daily life and ruining the service quality. We propose a novel approach for spam message detection based on mining the underlying social network of SMS activities. Comparing with strategies on keywords or flow detection, our network-based approach is more robust and difficult to defeat by human spammers. Various levels of features are employed to describe multiple aspects of the network, such as static structures, node activities and evolving situations. Experimental results on real dataset illustrate effectiveness of various features, showing our promising results.

关键词： data mining electronic messaging feature extraction mobile computing network theory (graphs) social networking (online) unsolicited e-mail

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Cross-view object classification in traffic scene surveillance based on transductive transfer learning

Cross-view object classification in traffic scene surveillan...

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IEEE International Conference on image processing

作者： Yi Mo Zhaoxiang Zhang Yunhong Wang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University Beijing China

Object classification in traffic scene surveillance has been a hot topic in image processing field. A big challenge is that shooting view changes in different scenes, which leads to sharp accuracy decrease since training and test samples do not share the same distribution. Inductive transfer learning methods try to bridge this gap by making use of manually labeled target samples. However, it is in line with reality to conduct unsupervised transfer without manually labeling. In this paper, we propose an intuitive transductive transfer method by transferring instances across view. Experimental results indicate that our method outperforms traditional approaches such as inductive SVM and cluster method, and could even achieve a comparable performance compared with manually labeling approach.

关键词： Support vector machines Surveillance Training Accuracy Labeling image edge detection Feature extraction

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A hierarchical framework for image-based human age estimation by weighted and OHRanked Sparse Representation-based classification

A hierarchical framework for image-based human age estimatio...

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IAPR International Conference on Biometrics (ICB)

作者： Weixin Li Yunhong Wang Zhaoxiang Zhang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University Beijing China

Human age estimation based on face images can figure in a wide variety of real-world applications. In this paper, we propose a novel and efficient facial age estimation algorithm which decides human age in a hierarchical framework. Biologically, human lives can be roughly divided into two stages, the period from birth to adulthood and the period from adulthood to old age, which are quite different from each other in face growth and aging forms. Considering that craniofacial growth occurs mainly in the first stage while keeps basically stable in the second, based on the shape features, the coarse step of the framework determines which age stage the test sample belongs to using a quadratic function. On the other hand, since the face appearance of individuals in the same age group or even of the same age does have some similarities in common, accurate age estimation within the age stage is solved by Sparse Representation-based classification (SRC) in the fine step. However, SRC requires sufficient training samples in each class and in practice this assumption often does not hold, making the performance of age estimation limited. Accordingly, we take use of the idea of Ordinal Hyperplanes Ranker (OHRank) and weights of samples' numbers in each class to solve the aforementioned problem, improving the age estimation results. Results of experiments conducted on the FG-NET Database demonstrate the effectiveness of our method.

关键词： Face Estimation Training Shape Aging Feature extraction Humans

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An application of circumscribed circle filter in the multi-stencils fast marching method 12

An application of circumscribed circle filter in the multi-s...

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27th Annual ACM Symposium on Applied Computing, SAC 2012

作者： Liu, Hong Hung, Chih-Cheng Hu, Huaifei Yu, Mali Song, Enmin School of Computer Science Huazhong University of Science and Technology Wuhan China Key Laboratory of Education Ministry for Image Processing and Intelligent Control Wuhan Hubei 430074 China School of Computing and Software Engineering Southern Polytechnic State University Marietta GA 30060 United States

ISBN: (纸本)9781450308571

We develop an effective method for improving the segmentation result based on the Multi-Stencils Fast Marching method (MSFM). In MSFM, the gradient information of the image plays a vital role for calculating edges. It is straightforward to obtain the edge of good quality images;however, MSFM may not have robust edge maps available for images with spurious edges. Thus, a special multi-direction circumscribed circle filter is proposed to calculate the image gradient information which is then used in the MSFM. Using the new gradient information, better image contours can be obtained with MSFM. The size of the radius used in our circle filter is constant even the standard deviation of zero-mean Gaussian noise changes while the parameters of mean filter and Canny filter for gradient computation have to be correctly selected according to different noisy images. Our proposed method shows that it is effective through the experiments of image segmentation. © 2012 ACM.

关键词： image segmentation

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Asynchronous extended spiking neural P systems with astrocytes

Asynchronous extended spiking neural P systems with astrocyt...

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12th International Conference on Membrane Computing, CMC 2011

作者： Pan, Linqiang Wang, Jun Hoogeboom, Hendrik Jan Image Processing and Intelligent Control Key Laboratory of Education Ministry Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China Leiden Institute of Advanced Computer Science Universiteit Leiden Niels Bohrweg 1 2333 CA Leiden Netherlands

ISBN: (纸本)9783642280238

A variant of spiking neural P systems was recently investigated by the authors, using astrocytes that have excitatory and inhibitory influence on synapses. In this work, we consider this system in the non-synchronized (i.e., asynchronous) mode: in any step, when a neuron is enabled, it is not obligatorily fired, making a global clock dispensable. It is proved that asynchronous spiking neural P systems with astrocytes are universal (when using extended rules). The construction is uniform in the sense that the form of the modules used is independent of the simulated register machine. © 2012 Springer-Verlag.

关键词： Artificial intelligence

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Pan-sharpening using weighted red-black wavelet

Pan-sharpening using weighted red-black wavelet

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International Conference on Pattern Recognition

作者： Qingjie Liu Yunhong Wang Zhaoxiang Zhang Lining Liu Intelligent Recognition and Image Processing Lab Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9781467322164

In this paper, we propose a new method for remote sensing image pan-sharpening which is based on weighted red-black (WRB) wavelet and adaptive principal component analysis (PCA), where the adaptive PCA is used to reduce spectral distortions and the utilization of WRB wavelet is used to extract the spatial details in PAN images. To reduce the artifacts and spectral distortions in the pan-sharpened images, which were caused by the local instabilities and dissimilarities in the PAN and MS images, a local process strategy incorporating detail enhancement is introduced. The proposed method is tested on two datasets both acquired by QuickBird and compared with the existing methods. Experimental results show that our method can provide promising fused MS images at a high spatial resolution.

关键词： Principal component analysis Correlation Remote sensing Multiresolution analysis Spatial resolution Discrete wavelet transforms

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Enhancing biometric security with wavelet quantization watermarking based two-stage multimodal authentication

Enhancing biometric security with wavelet quantization water...

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International Conference on Pattern Recognition

作者： Bin Ma Chunlei Li Yunhong Wang Zhaoxiang Zhang Di Huang Intelligent Recognition and Image Processing Lab Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9781467322164

In this paper we propose a watermarking based two-stage authentication framework to enhance biometric system security. The face feature of one individual is embedded into his/her fingerprint image as credibility token. During authentication, the watermark is first extracted to establish data authenticity. If legitimate, the face pattern can further serve as supplemental trait in biometric authentication progress. A wavelet quantization based watermarking method is proposed to robustly embed information in fingerprints while preserving their discriminating features. Meanwhile, a sparse representation based classifier is adopted to efficiently exploit the identity information within face watermarks. Experimental results which evaluate both watermarking and biometric authentication performance demonstrate the effectiveness of this work.

关键词： Watermarking Face Authentication Robustness Quantization Pattern recognition

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Displacement prediction model of landslide based on ensemble of extreme learning machine

Displacement prediction model of landslide based on ensemble...

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19th International Conference on Neural Information processing, ICONIP 2012

作者： Lian, Cheng Zeng, Zhigang Yao, Wei Tang, Huiming Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hubei China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan Hubei China School of Computer Science South-Central University for Nationalities Wuhan Hubei China Faculty of Engineering China University of Geosciences Wuhan Hubei China

ISBN: (纸本)9783642344770

Based on time series analysis, total accumulative displacement of landslide is divided into the trend component displacement and the periodic component displacement according to the response relation between dynamic changes of landslide displacement and inducing factors. In this paper, a novel neural network technique called the ensemble of extreme learning machine (E-ELM) is proposed to investigate the interactions of different inducing factors affecting the evolution of landslide. Trend component displacement and periodic component displacement are forecasted respectively, then total predictive displacement is obtained by adding the calculated predictive displacement value of each sub. A case study of Baishuihe landslide in the Three Gorges reservoir area is presented to illustrate the capability and merit of our model. © 2012 Springer-Verlag.

关键词： Landslides

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A novel segmentation method for convex lesions based on dynamic programming with local intra-class variance 12

A novel segmentation method for convex lesions based on dyna...

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27th Annual ACM Symposium on Applied Computing, SAC 2012

作者： Yu, Mali Huang, Qiliang Jin, Renchao Song, Enmin Liu, Hong Hung, Chih-Cheng School of Computer Science Huazhong University of Science and Technology Wuhan China Key Laboratory of Education Ministry for Image Processing and Intelligent Control Wuhan Hubei China Radiology Department Second People's Hospital of Nanning Nanning China School of Computing and Software Engineering Southern Polytechnic State University GA United States

ISBN: (纸本)9781450308571

Lesion segmentation plays an important role in medical image processing and analysis. There exist several successful dynamic programming (DP) based segmentation methods for general images. In those methods, the gradient is used as an important factor in the cost function to attract the contours to the boundaries. Since medical images have their characteristics such as low contrast, blurred edges and high noises, the gradient operator cannot work well enough to achieve a satisfactory performance for boundary detection. We define the local intra-class variance and combine it with the dynamic programming method to replace the traditional gradient operation. Experiments on synthetic and X-ray images are carried out and the results are compared with Canny and fast multilevel fuzzy edge detection (FMFED) algorithms. It is demonstrated that the proposed method performs better on medical images with low contrast, blurred edges and high noises. In addition, 483 regions of interest of mammograms randomly extracted from DDSM of the University of South Florida are used to compare our proposed method with the plane-fitting and dynamic programming method (PFDP), and the normalized cut segmentation method (Ncut). The results demonstrate that our method is more accurate and robust than PFDP and Ncut. © 2012 ACM.

关键词： Dynamic programming

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Improved cross-media relevance model for automatic image annotation

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ICIC Express Letters, Part B: Applications 2012年第5期3卷 1231-1237页

作者： Song, Haiyu Li, Xiongfei Wang, Pengjie Bao, Cuizhu Liu, Yongkui Xu, Lu Institute of Computer Graphics and Image Processing Dalian Nationalities University No. 18 Liaohe Road Economic and Technological Development Zone-Dalian 116600 China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Jilin University No. 2699 Qianjin Avenue Changchun 130012 China

Automatic image annotation has been an active research topic in the last decade due to its potentially large impact on image retrieval, object recognition and image understanding. Many approaches have been proposed for image annotation in recent years. The most influential annotation model is relevance model, whose representative algorithm is Cross-Media Relevance Model (CMRM). In this paper, to overcome the shortcomings of the original CMRM, we propose improved CMRM. In the improved CMRM, the annotation word distribution is estimated using binary probability, the significance of blob is discriminately depicted using TF-IDF (term frequency-inverse document frequency) schemes, and the similarity measurement of blob is based on blob and continuousvalued feature vector. The experimental results on the standard Corel5K dataset show that our proposed approach outperforms the original CMRM by about 111% and 73% in terms of F1 and N+ measures respectively. The improved CMRM can get better performance in specific domains such as cultural heritage and special necessities digitization for ethnic minorities. © 2012 ICIC International.

关键词： image retrieval

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