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检索条件"任意字段=6th International Conference on Wavelet Analysis and Pattern Recognition"

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wavelet PACKETS-BASED ROBUST BLIND DIGITAL WATERMARK SCHEME

WAVELET PACKETS-BASED ROBUST BLIND DIGITAL WATERMARK SCHEME

引用

6th international conference on wavelet analysis and pattern recognition

作者： Jin, Cong Jin, Shu-Wei Cent China Normal Univ Dept Comp Sci Wuhan 430079 Peoples R China Cent China Normal Univ No Middle Sch 1 Wuhan 430079 Peoples R China

ISBN: (纸本)9781424422388

A wavelet packets-based robust blind watermark scheme using chaotic encryption is proposed in this paper. Two chaotic sequences are modulated according characters of chaotic system, using for sub image extraction and watermark encryption. the binary watermark information is changed into one dimension sequence by module arithmetic. An encrypted watermark sequence can get after do XOR arithmetic with the sequence and a binary chaotic sequence after modulating. For embedding watermark, partition the original image into 8x8 blocks, extract sub image about one-fourth of total original image blocks by another chaotic sequence then wavelet packet decomposition is applied for it. Embed watermark by using relationships of wavelet packet coefficients. It realizes a blind extraction because extraction watermark doesn't need original image. the experiment results show that proposed scheme is very robust against for various attacks such as JPEG compression, Gaussian noise, cropping and scaling, etc.

关键词： Blind extraction Chaotic sequence Sub image Watermark wavelet packet

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IMPROVED FORWARD FLOATING SELECTION ALGORIthM FOR FEATURE SUBSET SELECTION

IMPROVED FORWARD FLOATING SELECTION ALGORITHM FOR FEATURE SU...

引用

6th international conference on wavelet analysis and pattern recognition

作者： Nakariyakul, Songyot Casasent, David P. Thammasat Univ Dept Elect & Comp Engn 99 Moo 18 Phaholyothin RdAmpher Khlongluang Pathum Thani 12120 Thailand Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA

ISBN: (纸本)9781424422388

We present results on two new databases for a new improved forward floating selection (IFFS) algorithm for selecting a subset of features. the algorithm is an improvement upon the state-of-the-art sequential forward floating selection algorithm that includes a new search strategy to check whether removing any feature in the selected feature set and adding a new one at each sequential step can improve the resultant feature set. We find that this method provides the optimal or quasi-optimal (close to optimal) solutions for many selected subsets and requires significantly less computational load than an exhaustive search optimal feature selection algorithm. Our experimental results for two different databases demonstrate that our algorithm consistently selects better subsets than other quasi-optimal feature selection algorithms do.

关键词： Dimensionality reduction Feature selection Floating feature selection pattern recognition

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RESEARCH OF VISION recognition ON AUTO RACK GIRDERS BASED ON IMPROVED ART2 NEURAL NETWORK AND D-S EVIDENCE thEORY

RESEARCH OF VISION RECOGNITION ON AUTO RACK GIRDERS BASED ON...

引用

6th international conference on wavelet analysis and pattern recognition

作者： Han, Li-Qiang Wang, Hua Gao, Ji-Gang Zhang, Shuang Changchun Inst Technol Coll Mech Sci & Engn Changchun 130012 Peoples R China

ISBN: (纸本)9781424422388

For type's recognition of camion rack girders, this paper puts forward a pattern recognition method based on improved ART2 neural network and D-S evidence theory. Firstly, for collected auto rack girders top images, region is partitioned to 16 equal regions (4x4), which covers high-frequency wavelet coefficient with one-layer wavelet transform, and gained local variance of wavelet coefficient in every sub-region is used as a character template;in the same way, is partitioned to 16 sub-images (4x4), estimating numbers of gray value "1" in every sub-region, to gain the area character template. Secondly, data of two character templates are used as inputs of improved ART2 neural network, to gain data of joint weights of network, and the basal confidence m(2), m(2). Finally, gain the total confidence with composition rule of D-S evidence theory, according to the maximum of the total confidence, to recognize types of auto rack girders. Experiments indicate this algorithm may solve on-line vision recognition on hundreds of auto rack girders very well, and possesses advantage of more rapid, more precise and more reliable etc. Type's recognition of camion rack girders has a more broad application future and higher practicality, based on neural network and D-S evidence theory.

关键词： wavelet coefficient pattern recognition Improved ART2 neural network D-S evidence theory Character template

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wavelet ENERGY SIGNATURE AND GLCM FEATURES-BASED FINGERPRINT ANTI-SPOOFING

WAVELET ENERGY SIGNATURE AND GLCM FEATURES-BASED FINGERPRINT...

引用

6th international conference on wavelet analysis and pattern recognition

作者： Nikam, Shankar Bhausaheb Agarwal, Suneeta Motilal Nehru Natl Inst Technol Dept Comp Sci & Engn Allahabad 211004 Uttar Pradesh India

ISBN: (纸本)9781424422388

this paper proposes a texture-based method to spoof-proof a fingerprint biometric system. the fundamental basis of this anti-spoofing method is that, real fingerprint exhibits different textural characteristics from a spoof one. Textural measures based on wavelet energy signatures and gray level co-occurrence matrix (GLCM) features are used to characterize fingerprint texture. Dimensionalities of the feature sets are reduced by running Pudil's Sequential Forward Floating Selection (SFFS) algorithm. We test two feature sets independently on various classifiers like: AdaBoost.M1, support vector machine and OneR. then, we fuse all the mentioned classifiers using the "Product Rule" to form a hybrid classifier. Classification rates achieved for wavelet energy signatures range from similar to 94.35% to similar to 96.71%. Likewise, classification rates for GLCM features range from similar to 94.82% to similar to 97.65%. thus, the performance of a proposed method is very promising and it can be efficiently used to spoof-proof a real-time fingerprint biometric system.

关键词： Fingerprints Gray Level Co-occurrence matrix Liveness Texture wavelets

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pattern recognition Techniques Applied to Electric Power Signal Processing

Pattern Recognition Techniques Applied to Electric Power Sig...

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6th international conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)

作者： Bousaleh, Ghazi Darwiche, Mohamad Hassoun, Fahed Lebanese Univ Saida Lebanon Eseo Inst Sci & Technol Angers France France Telecom Nantes France

ISBN: (纸本)9781467316583

We propose in this paper an approach whose main objective is to detect disturbances that affect an electric power signal. the method allows us to locate the time occurrence of these disturbances. the signal processing consists of determining two distributions that are based on the energy of the wavelet signal decomposition: the deviation distribution and the deformation distribution. theses distributions are a signature of the disturbance and are able to provide an identification of the type of the problem. the method has been developed using the analysis by the Discrete wavelet Transform (DWT). the electrical signal is decomposed into several levels by DWT. the different waveforms resolution levels allows us to detect any deviations from the sane signal. the energy distributions data obtained in the first step will be used as feature vectors for training an artificial neural network (ANN) with multilayer perceptrons (MLPs) and support vector machines (SVMs) to classify the Power Quality Disturbance (PQD).

关键词： multilayer perceptrons pattern recognition power engineering computing power supply quality signal resolution support vector machines wavelet transforms

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Face recognition Based on Fusion of Multiple Masks Local Feature Sets Using wavelet Transform 6

Face Recognition Based on Fusion of Multiple Masks Local Fea...

引用

6th international conference and Workshops on Recent Advances and Innovations in Engineering (ICRAIE)

作者： Al-Dabagh, Mustafa Zuhaer Nayef Ahmad, Muhammad Imran Anwar, Said Amirul Univ Malaysia Perlis Fac Elect Engn Technol Perlis Malaysia Knowledge Univ Dept Comp Sci Erbil Iraq

ISBN: (纸本)9781665434027

Although face recognition confronts several challenges, it has garnered considerable attention over the last two decades. A new proposal of local directional pattern (LDP) operator for face recognition has been introduced to overcome different challenges confronting face recognition systems. this new proposal is known as Multi-Mask Local Directional pattern (MMLDP), which integrates the advantages of LDP operator depending on Robinson and Kirsch masks into one feature vector to give more discrimination information. Firstly, the LDP operator applies various masks to obtain the face image feature, and after that, methods such as Left-Right fusion, Right-Left fusion, Down-Up fusion, and Up-Down fusion are used to fuse the features. Finally, by employing a support vector machine (SVM), the classification of the feature ensues. the conducted experiments utilized the Yale database, and outcomes show that fusion of the features for various masks based on LDP improved performance with the best classification accuracy of 94.2857% compared to LDP and other conventional approaches for face recognition.

关键词： Face recognition Local Directional pattern Kirsch mask Robinson Mask wavelet Transform

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TWO-DIMENSIONAL LOCALITY SENSITIVE DISCRIMINANT analysis

TWO-DIMENSIONAL LOCALITY SENSITIVE DISCRIMINANT ANALYSIS

引用

6th international conference on wavelet analysis and pattern recognition

作者： Wei, Yantao Li, Hong Xia, Tian Huazhong Univ Sci & Technol Inst Pattern Recognit & Artifcial Intelligence Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Math & Stat Wuhan 430074 Peoples R China Univ Adelaide Dept Comp Sci Adelaide SA 5005 Australia

ISBN: (纸本)9781424422388

Recently, locality sensitive discriminant analysis (LSDA) was proposed for dimensionality reduction. As far as matrix data, such as images, they are often vectorized for LSDA algorithm to rind the intrinsic manifold structure. Such a matrix-to-vector transform may cause the loss of some structural information residing in original 2D images. Firstly, this paper proposes an algorithm named two-dimensional locality sensitive discriminant analysis (2DLSDA), which directly extracts the proper features from image matrices based on LSDA algorithm. And the experimental results on the ORL database show the effectiveness of the proposed algorithm. After that, 2DLSDA plus Fisherface, which was presented for the further dimensionality reduction, was compared with other dimention reduction methods, namely Eigenface, LSDA and 2DLSDA plus PCA. Experiments show that conducting Fisherface after 2DLSDA achieves high recognition accuracy.

关键词： Manifold learning Locality sensitive discriminant analysis Two-dimensional locality sensitive discriminant analysis Face recognition

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ACTIVE CONTROL EXPERIMENTAL BASED ON wavelet analysis

ACTIVE CONTROL EXPERIMENTAL BASED ON WAVELET ANALYSIS

引用

6th international conference on wavelet analysis and pattern recognition

作者： Ma, Qian-Ying Wang, She-Liang Zhang, Cheng-Zhong Zhu, Jun-Qiang Xian Univ Architecture & Technol Coll Civil Engn Xian 710055 Peoples R China

ISBN: (纸本)9781424422388

Traditional method of structural vibration control through stiffen the components, decoupling the harmonic resonance system, vibration and damping isolation, or dynamic vibration absorb, all rely structure damping consumption the energy, the control effect is limited because the constraints of materials performance. Piezoelectric smart structure with advantages such as fast response, arrangement flexible, not only can be sensors, but also can be actuators, so it play a positive and effective role in vibration control, and gain more and more attention of scientific researchers and designers. the active control becoming the main means in the structure vibration control, one core of active control is the control law between input and output, because its designs based on the reduced-order model, in addition to meet the performance of dynamic stability and dynamic response, but also has good robustness, which is not sensitive for the closed-loop system of the control parameters and controlled targets. this paper based on a active control tests, using wavelet scaling function approximation with the ability to filter out high frequency components, built a piezoelectric actuator control dynamic model by displacement and velocity feedback signal, which solution the instability problem caused by the overflow observation and control overflow coupling, and it be in the actual application and verify in the experimental.

关键词： wavelet analysis Active Control Overflow Feedback Signal

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An Intelligent and Robust Multi-Oriented Image Scene Text Detection 6

An Intelligent and Robust Multi-Oriented Image Scene Text De...

引用

6th international conference on Soft Computing and pattern recognition (SoCPaR)

作者： Sayahi, Salem Ben Halima, Mohamed Univ Gabes Gabes Tunisia Univ Sfax REGIM Lab Res Grp Intelligent Machines ENIS BP 1173 Sfax 3038 Tunisia

ISBN: (纸本)9781479959341

Text in image is an important source of information. In this article, we describe an approach for detection of text in the scene file. Our method classify pixels into text and non-text areas using neural network and wavelet transformation. It is divided into two steps: a step offline and online step. the experimental results show the performance of our algorithm.

关键词： Text detection wavelet Neural Network

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A VQ-BASED FAST FACE recognition ALGORIthM USING OPTIMIZED CODEBOOK

A VQ-BASED FAST FACE RECOGNITION ALGORITHM USING OPTIMIZED C...

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6th international conference on wavelet analysis and pattern recognition

作者： Chen, Qiu Kotani, Koji Lee, Fei-Fei Ohmi, Tadahiro Tohoku Univ New Ind Creat Hatchery Ctr Aoba Ku Aza Aoba 6-6-10 Sendai Miyagi 9808579 Japan Tohoku Univ Grad Sch Engn Dept Elect Aoba Ku Sendai Miyagi 9808579 Japan

ISBN: (纸本)9781424422388

In this paper, we present a VQ-based fast face recognition algorithm using an optimized codebook. Previously, Chen et al. 1161 proposed a novel codebook design method based on the systematic classification and organization of code patterns abstracted from facial images for reliable face recognition. In this paper, an improved codebook design method is proposed. Combined by a systematically organized codebook based on the classification of code patterns and another codebook created by Kohonen's Self-Organizing Maps (SOM), an optimized codebook consisted of 2x2 codevectors for facial images is generated. We demonstrate the performance of our algorithm using publicly available AT&T database containing variations in lighting, posing, and expressions. Compared with the algorithms employing original codebook or SOM codebook separately, experimental results show face recognition using the optimized codebook is more efficient. the highest average recognition rate of 98.2% is obtained for 40 persons' 400 images of AT&T database. A table look-up (TLU) method is also proposed for the speed up of the recognition processing in this paper. By applying this method in the quantization step, the total recognition processing time achieves only 28 msec, enabling real-time face recognition.

关键词： Face recognition Vector quantization Codebook pattern classification SOM

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