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Template selection for on-line signature verification

Template selection for on-line signature verification

引用

International Conference on Pattern recognition

作者： Ningning Liu Yunhong Wang Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering BeiHang University Beijing China

ISBN: (纸本)9781424421749

In this paper, we propose two effective methods to perform automatic template selection where the goal is to select prototype signature templates for a user from a given set of online signatures. The first method employs a clustering strategy to choose a template set that best represents the intra-class variations, while the second method selects templates that exhibit maximum similarity with the rest of the signatures. In the experiment, two typical online signature verification have been employed, respectively based on global and local features, and the verifying results on a database Task2 of SVC2004 (First Signature Verification Competition 2004), with 20 genuine signatures and 20 skilled forgeries for each set, indicate that two proposed selection procedures as presented here results in better performance than random template selection.

关键词： Handwriting recognition Prototypes Shape measurement Writing image recognition image processing laboratories Computer science Design engineering Spatial databases

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Gender recognition based on fusion on face and gait information

Gender recognition based on fusion on face and gait informat...

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： De Zhang Yun-Hong Wang Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing China

This paper considers the combination of face and gait biometrics from the same walking sequence to carry out gender recognition. A camera is capturing the side view of a person, while another camera is placed to record the face of the same person at the front view. After these videos are acquired, we extract the silhouette images from the gait videos and normalized frame images decomposed from the face videos. Then, for face classification, we introduce PCA to reduce the image dimension and SVM to classify gender, for gait classification, we divide the silhouette into seven parts and extract features from each and also employ SVM to classify gender. On the decision level, the sum rule is applied to implement the fusion of these two classification results. The final fusion results show an improvement on correct classification rate.

关键词： Face Support vector machines Cameras Principal component analysis Feature extraction Face recognition Databases

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Investigating the separability of features from different views for gait based gender classification

Investigating the separability of features from different vi...

引用

International Conference on Pattern recognition

作者： De Zhang Yunhong Wang Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering BeiHang University Beijing China

ISBN: (纸本)9781424421749

In this paper, we investigate the efficiency of different view angles when classifying gender with gait biometrics for the first time. A gait database is built for this purpose in which walking videos are recorded at seven different views for each subject. Then, we employ a robust gait representation method to extract gait features. The class separability of these features from different view angles are analyzed and compared. A set of experiments are designed to evaluate the performance of gait based gender classification along with the changes of view angle. The experimental results show that 0deg and 180deg are the worst view angles in this two-category case and the 90deg view dose not perform the best, unlike it takes the best performance in gait recognition.

关键词： Humans Legged locomotion Spatial databases Biometrics Robustness Feature extraction Data analysis Data mining image recognition image processing

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FUSION OF GLOBAL AND LOCAL INFORMATION FOR AN ON-LINE SIGNATURE VERIFICATION SYSTEM

FUSION OF GLOBAL AND LOCAL INFORMATION FOR AN ON-LINE SIGNAT...

引用

2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

作者： NING-NING LIU YUN-HONG WANG Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing 100083 China

In this paper, an on-line signature verification system exploiting local and global information using two-stage fusion is presented. At the first stage, global information is extracted as I3-dimensional vector and recognized by Majority Classifiers, and then local information is extracted as time functions of various dynamic properties and recognized by BP neural network classifier. By fusing global and local information and introducing an enhanced dynamic time warping algorithm and a normalized feature measure, our method obtained an average EER of 4.02％ on public database SVC2004( First Signature Verification Competition 2004) Task2 compared to 6.90％ the first place at SVC2004.

关键词： Biometrics online signature verification DTW algorithm two stage fusion

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Comparing and integrating alignment template and standard phrase-based statistical machine translation

Comparing and integrating alignment template and standard ph...

引用

8th International Conference on intelligent Text processing and Computational Linguistics

作者： Xu, Lin Cao, Xiaoguang Zhang, Bufeng Li, Mu Lab. of Pattern Recognition and Intelligent System Image Processing Center BeiHang University China Al Lab. Computer Science and Technology Tianjing University China Microsoft Research Asia China

ISBN: (纸本)9783540709381

In statistical machine translation (SMT) research, phrase-based methods have been receiving more interest in recent years. In this paper, we first give a brief survey of phrase-based SMT framework, and then make detailed comparisons of two typical implementations: alignment template approach and standard phrase-based approach. At last, we propose an improved model to integrate alignment template into standard phrase-based SMT as a new feature in a log-linear model. Experimental results show that our method outperforms the baseline method.

关键词： Natural language processing systems

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HUMAN GAIT recognition BASED ON X-T PLANE ENERGY imageS

HUMAN GAIT RECOGNITION BASED ON X-T PLANE ENERGY IMAGES

引用

2007 International Conference on Wavelet Analysis and Pattern recognition (ICWAPR 2007), vol.3

作者： GUO-CHANG HUANG YUN-HONG WANG Intelligent Recognition and Image Processing Laboratory Beihang University Beijing China

In this paper, we propose a novel algorithm for gait recognition. Binarized silhouette of a motion object is first segmented from color image, and then, spatio-temporal (XYT) volume is constructed by using these binarized silhouettes, and cut at knee and hip height. Next, energy images are extracted by projecting these three individual XYT volumes onto X-T plane, respectively. Fourier Transform is employed as a processing step to achieve translation invariant for the silhouette sequences which are captured from the subjects walk in different speed. Then three frequency-domain feature vectors are fused. AdaBoost is used to select a small set of critical features from all of the features. Nearest Neighbor and Support Vector Machine (SVM) classifier are finally executed to produce final decision, respectively. The experiments are carried on one of the largest public gait database: the CASIA database. The experimental results show that the proposed algorithm is efficient for human gait recognition, and achieves competitive performance.

关键词： Biometrics Gait Gait recognition Adaboost

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On-line signature verification based on fusion of global and local information

On-line signature verification based on fusion of global and...

引用

International Conference on Wavelet Analysis and Pattern recognition (ICWAPR)

作者： Lei Hu Yun-Hong Wang Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing China

Automatic signature verification has been an intense research area because of the social and legal acceptance and widespread use of written signatures. It is still a challenging issue because of "small sample size " problem as well as large intra-class variations and, when considering forgeries, small inter-class variations. In order to solve these problems, we propose a two-stage fusion method to get high accuracy. At first, an EDTW (enhanced dynamic time warping) algorithm and a normalized feature measure are proposed to build a classifier based on local features. The former enhances the separability between genuine and forgery signatures, while the latter approaches the problem as a two-class pattern recognition problem, which make it possible to use training signatures as many as possible. However, local method is time and resource consuming, so we then design another classifier based on global features using majority voting rule. We fuse the global and local method by two-sage serial strategy to build an on-line signature verification system. Experimental results on SVC2004 TASK2 show good performance of our system.

关键词： Handwriting recognition Pattern recognition Forgery Voting Wavelet analysis Pattern analysis Law Legal factors Fuses

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Carrying object detection and tracking based on body main axis

Carrying object detection and tracking based on body main ax...

引用

International Conference on Wavelet Analysis and Pattern recognition (ICWAPR)

作者： Yue Qi Guo-Chang Huang Yun-Hong Wang Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing China

In this paper, we propose a method to examine whether a walking person is carrying objects using the width of human body contour. First we concentrate on the detection of the moving people contour and then human contour width is projected to the feature space for training a classifier. We introduce principal component analysis for dimension reduction and support vector machine to classify the carrying object status. If the status is true, the carrying object region is figured out by analyzing human contour shape. We utilize the outmost vertex from human contour to track the carrying object such as a rucksack or luggage. The experimental results demonstrate that our approach is encouraging.

关键词： Object detection Humans Principal component analysis Support vector machines Feature extraction Video sequences Pattern recognition Legged locomotion Filtering Wavelet analysis

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A robust infrared face recognition method based on adaboost gabor features

A robust infrared face recognition method based on adaboost ...

引用

International Conference on Wavelet Analysis and Pattern recognition (ICWAPR)

作者： Di Huang Yun-Hong Wang Yi-Ding Wang Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing China Chinese Academy of Sciences Beijing China

Face recognition is one of the most successful applications in biometric authentication. However, methods reported in the literature are far from perfect and deteriorate ungracefully where lighting condition cannot be controlled. This paper presents a new robust method for face recognition under near infrared lighting condition based on AdaBoost Gabor features with linear discriminant analysis classification (ALGabor), which solves the problems produced by variations of illumination rightly, since the NIR images are insensitive to variations of environmental lighting, and Gabor wavelets can extract adequate features form the images. To gain the qualified NIR images, a device has been designed. Gabor wavelets are used to extract the features form the NIR images. Although Gabor feature vectors often have very high dimensions, a classifier has been trained using the AdaBoost algorithm to select the most representative feature. Compared with the huge number of features produced by typical Gabor wavelets, the classifier in this paper only selects hundreds of features, which saves computation and time cost significantly. The comparison between the results of the method in this paper and several classic algorithms proves the effectiveness of the proposed method.

关键词： Robustness Face recognition Feature extraction Biometrics Authentication Lighting control Infrared imaging Linear discriminant analysis Wavelet analysis Computational efficiency

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Color image filtering based on impulsive noise detection

Color image filtering based on impulsive noise detection

引用

MIPPR 2007: Automatic Target recognition and image Analysis;and Multispectral image Acquisition

作者： Li, Dehua Jin, Lianghai Yao, Xingzhong Xiong, Caiquan State Key Lab. for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Second Artillery Command College Wuhan 430012 China School of Computer Science Hubei University of Technology Wuhan 430068 China

ISBN: (纸本)9780819469502

This paper introduces a new class of switching vector median filter. The proposed algorithm first uses four directional masks to analyze the color difference between the central pixel and its neighborhood pixels in the RGB color space and classify each color pixel into noisy pixel or noise-free one, and then employs the standard vector median filtering operations in the detected noisy locations to restore the corrupted pixels and leave the noise-free ones unchanged. The simulation results show that the proposed method excellently suppresses impulsive noise as well as preserving the image details well, and significantly outperforms the existing vector filtering solutions in terms of both the objective measures and the perceptual visual quality.

关键词： Color image processing

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