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10th IEEE Singapore International Conference on Communications Systems, ICCS 2006

作者： Ngo, Hau T. Asari, Vijayan K. Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA 23529 United States

ISBN: (纸本)1424404118

Design of a low power Multiply-and-Accumulator (MAC) unit for video processing systems exploiting the similarity of neighboring pixels in video streams is presented in this paper. The proposed technique minimizes dynamic power consumption by analyzing the bit patterns in the input data to reduce switching activities. Special values of the pixels in the video streams such as zero, one, repeated values or repeated bit combinations are detected and control signals are generated to bypass the data and to reuse the results in the MAC unit. It is observed that the proposed scheme helps to reduce operations and switching activities in the MAC unit up to 30% which results in lower power consumption with minimal hardware overhead. © 2006 IEEE.

关键词： Pixels

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Gabor wavelet based modular PCA approach for expression and illumination invariant face recognition

Gabor wavelet based modular PCA approach for expression and ...

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35th Applied Imagery and Pattern Recognition Workshop, AIPR 2006

作者： Gudur, Neeharika Asari, Vijayan Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA 23529-0246 United States

ISBN: (纸本)0769527396

A Gabor wavelet based Modular PCA approach for face recognition is proposed in this paper. The proposed technique improves the efficiency of face recognition, under varying illumination and expression conditions for face images when compared to traditional PCA techniques. In this algorithm the face images are divided into smaller sub-images called modules and a series of Gabor wavelets at different scales and orientations are applied on these localized modules for feature extraction. A modified PCA approach is then applied for dimensionality reduction. Due to the extraction of localized features using Gabor wavelets, the proposed algorithm is expected to give improved recognition rate when compared to other traditional techniques. The performance of the proposed technique is evaluated under conditions of varying illumination, expression and variation in pose up to a certain range using standard face databases. © 2006 IEEE.

关键词： Face recognition

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A Dialectal Chinese Speech Recognition Framework

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Journal of computer science & Technology 2006年第1期21卷 106-115页

作者：李净郑方 William Byrne Dan Jurafsky Center for Speech Technology State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing 100084 P.R. China Machine Intelligence Laboratory Cambridge University U.K. Center for Language and Speech Processing The Johns Hopkins University U.S.A. Department of Linguistics Stanford University U.S.A.

A framework for dialectal Chinese speech recognition is proposed and studied, in which a relatively small dialectal Chinese （or in other words Chinese influenced by the native dialect） speech corpus and dialect-related knowledge are adopted to transform a standard Chinese （or Putonghua, abbreviated as PTH） speech recognizer into a dialectal Chinese speech recognizer. Two kinds of knowledge sources are explored： one is expert knowledge and the other is a small dialectal Chinese corpus. These knowledge sources provide information at four levels： phonetic level, lexicon level, language level, and acoustic decoder level. This paper takes Wu dialectal Chinese （WDC） as an example target language. The goal is to establish a WDC speech recognizer from an existing PTH speech recognizer based on the Initial-Final structure of the Chinese language and a study of how dialectal Chinese speakers speak Putonghua. The authors propose to use contextindependent PTH-IF mappings （where IF means either a Chinese Initial or a Chinese Final）, context-independent WDC-IF mappings, and syllable-dependent WDC-IF mappings （obtained from either experts or data）, and combine them with the supervised maximum likelihood linear regression （MLLR） acoustic model adaptation method. To reduce the size of the multipronunciation lexicon introduced by the IF mappings, which might also enlarge the lexicon confusion and hence lead to the performance degradation, a Multi-Pronunciation Expansion （MPE） method based on the accumulated uni-gram probability （AUP） is proposed. In addition, some commonly used WDC words are selected and added to the lexicon. Compared with the original PTH speech recognizer, the resulting WDC speech recognizer achieves 10-18% absolute Character Error Rate （CER） reduction when recognizing WDC, with only a 0.62% CER increase when recognizing PTH. The proposed framework and methods are expected to work not only for Wu dialectal Chinese but also for other dialectal Chinese languages and

关键词： dialectal Chinese speech recognition initial or final （IF） IF-mapping rule pronunciation modeling small quantity of speech data

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Autonomous learning of object appearances using colour contour frames

Autonomous learning of object appearances using colour conto...

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3rd Canadian Conference on computer and Robot vision, CRV 2006

作者： Forssén, Per-Erik Moe, Anders Laboratory for Computational Intelligence Department of Computer Science 2366 Main Mall BC V6T 1Z4 Canada Computer Vision Laboratory Department of Electrical Engineering Linköping University SE-581 83 Linköping Sweden

ISBN: (纸本)0769525423

In this paper we make use of the idea that a robot can autonomously discover objects and learn their appearances by poking and prodding at interesting parts of a scene. In order to make the resultant object recognition ability more robust, and discriminative, we replace earlier used colour histogram features with an invariant texture-patch method. The texture patches are extracted in a similarity invariant frame which is constructed from short colour contour segments. We demonstrate the robustness of our invariant frames with a repeatability test under general homography transformations of a planar scene. Through the repeatability test, we find that defining the frame using using ellipse segments instead of lines where this is appropriate improves repeatability. We also apply the developed features to autonomous learning of object appearances, and show how the learned objects can be recognised under out-of-plane rotation and scale changes. © 2006 IEEE.

关键词： Object recognition

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Classification with the hybrid of manifold learning and gabor wavelet

Classification with the hybrid of manifold learning and gabo...

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3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks

作者： Zhang, Junping Shen, Chao Feng, Jufu Shanghai Key Laboratory of Intelligent Information Processing Department of Computer Science and Engineering Fudan University Shanghai 200433 China Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing 100080 China National Key Laboratory for Machine Perception School of Electronics Engineering and Computer Science Peking University Beijing 100871 China

ISBN: (纸本)354034439X

While manifold learning algorithms can discover intrinsic low-dimensional manifold embedded in the high-dimensional Euclidean space, the discriminant ability of the low-dimensional subspaces obtained by the algorithms is often lower than those obtained by the conventional dimensionality reduction approaches. Furthermore, the original feature vectors may include redundancy such as high-order correlation which cannot be removed by manifold learning algorithms. To address the two problems, we first employ Gabor wavelet to remove intrinsic redundancies of images and obtain a set of over-completed feature vectors. Then a supervised manifold learning algorithm (ULLELDA) is applied to project Gabor-based data and out-of-the-samples into a common low-dimensional subspace. Experiments in two FERET face databases indicate that Gabors indeed help supervised manifold learning to remarkably improve the discriminant ability of low-dimensional subspaces. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Wavelet transforms

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Low Power Arithmetic Units for Video Processing Systems

Low Power Arithmetic Units for Video Processing Systems

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International Conference on Communication Systems

作者： Hau T. Ngo Vijayan K. Asari Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA USA

Design of a low power multiply-and-accumulator (MAC) unit for video processing systems exploiting the similarity of neighboring pixels in video streams is presented in this paper. The proposed technique minimizes dynamic power consumption by analyzing the bit patterns in the input data to reduce switching activities. Special values of the pixels in the video streams such as zero, one, repeated values or repeated bit combinations are detected and control signals are generated to bypass the data and to reuse the results in the MAC unit. It is observed that the proposed scheme helps to reduce operations and switching activities in the MAC unit up to 30% which results in lower power consumption with minimal hardware overhead

关键词： Arithmetic Energy consumption Frequency Clocks Capacitance Streaming media Dynamic voltage scaling Adders Hardware Circuits

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A Fully Pipelined Multiplierless Architecture for 2D Convolution with Quadrant Symmetric Kernels

A Fully Pipelined Multiplierless Architecture for 2D Convolu...

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IEEE Asia-Pacific Conference on Circuits and Systems

作者： Ming Z. Zhang Vijayan K. Asari Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA USA

Design of a fully pipelined multiplierless digital architecture for computing 2D convolution utilizing the quadrant symmetry of the kernels is proposed in this paper. Pixels in the four quadrants of the kernel region with respect to an image pixel are considered simultaneously for computing the partial results of the convolution sum. The new architecture performs computations in log-domain by utilizing low complexity log2 and inverse-log2 approximation modules. An effective data handling strategy is developed in conjunction with the logarithmic modules to eliminate the necessity of the multipliers in the architecture. The proposed architecture is capable of performing convolution operations for 181.3 1024 times 1024 frames or 190.1 million outputs per second with 22 times 22 kernels in a Xilinx's Virtex XC2V2000-4ff896 FPGA at maximum clock frequency of 190.1 MHz. The throughput of the new design is 3.17 times higher when compared with that of the previous implementations (Zhang et al., 2005). Evaluation in Xilinx's core generator showed that the proposed design results in 60% reduction in hardware resource when compared to the design using pipelined multipliers

关键词： Convolution Kernel computer architecture Pixel Data handling Field programmable gate arrays Clocks Frequency Throughput Hardware

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Design of a Digital Architecture for Real-Time Video, Enhancement Based on Illuminance-Reflectance Model

Design of a Digital Architecture for Real-Time Video, Enhanc...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Hau T. Ngo Ming Z. Zhang Li Tao Vijayan K. Asari Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA USA

A design of a high performance digital architecture for a nonlinear image enhancement technique is presented in this paper. The image enhancement is based on illuminance-reflectance model which improves the visual quality of digital images and video captured under insufficient or non-uniform lighting conditions [1]. Systolic, pipelined and parallel design techniques are utilized effectively in the proposed FPGA-based architectural design to achieve real-time performance. Estimation and folding techniques are used in the hardware algorithmic design to achieve faster, simpler and more efficient architecture. The video enhancement system is implemented using Xilinx's multimedia development board that contains a VirtexII-X2000 FPGA and it is capable of processing approximately 66 Mega-pixels (Mpixels) per second.

关键词： Signal processing algorithms Image enhancement Field programmable gate arrays Digital signal processing computer architecture Image coding Streaming media Parallel processing Reflectivity Algorithm design and analysis

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Design of a High Performance Digital Architecture for Real-Time Correction of Radial Lens Distortion

Design of a High Performance Digital Architecture for Real-T...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Hau T. Ngo Vijayan K. Asari Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA USA

The radial lens distortion correction technique based on least squares estimation corrects a distorted image by expanding it nonlinearly so that straight lines in the object space remain straight in the image space. An absolute pipelined architecture is designed to correct radial lens distortion in images by partitioning the distortion correction algorithm into four main modules. The architecture includes a COKDIC based rectangular to polar coordinate transformation module, a back mapping module for nonlinear transformation of corrected image space to distorted image space, a COKDIC based polar to rectangular coordinate transformation module, and a linear interpolation module to calculate the intensities of four pixels simultaneously in the corrected image space. The system parameters include the expanded/corrected image size, distorted image size, the back mapping coefficients, distortion center and the center of the corrected image. The hardware architecture can sustain a high throughput rate of 30 4-MegaPixel (Mpixels) frames per second (total of 120 Mpixels). The pipelined architecture design will facilitate the use of dedicated hardware that can be mounted along with the camera unit.

关键词： Optical design Lenses Nonlinear distortion Hardware Least squares approximation Algorithm design and analysis Partitioning algorithms Simultaneous localization and mapping Interpolation Pixel

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Gabor Wavelet Based Modular PCA Approach for Expression and Illumination Invariant Face Recognition

Gabor Wavelet Based Modular PCA Approach for Expression and ...

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Applied Imagery Pattern Recognition Workshop (AIPR)

作者： Neeharika Gudur Vijayan Asari Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University Norfolk VA USA

A Gabor wavelet based modular PCA approach for face recognition is proposed in this paper. The proposed technique improves the efficiency of face recognition, under varying illumination and expression conditions for face images when compared to traditional PCA techniques. In this algorithm the face images are divided into smaller sub-images called modules and a series of Gabor wavelets at different scales and orientations are applied on these localized modules for feature extraction. A modified PCA approach is then applied for dimensionality reduction. Due to the extraction of localized features using Gabor wavelets, the proposed algorithm is expected to give improved recognition rate when compared to other traditional techniques. The performance of the proposed technique is evaluated under conditions of varying illumination, expression and variation in pose up to a certain range using standard face databases.

关键词： Principal component analysis Lighting Face recognition Image recognition Feature extraction Vectors Statistical analysis Image databases Linear discriminant analysis Application software

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