检索结果-内蒙古大学图书馆

Bit-plane based contour information extraction for digital image

Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of technology 2010年第SUPPL. 2期42卷 110-113页

作者： Wu, Song-Lin Cui, Rong-Yi Intelligent Information Processing Lab. Department of Computer Science and Technology Yanbian University Yanji 133002 China

A bit-plane-based image contour information extracting method for histogram equalized image was proposed in this paper. Firstly, the influence of histogram equalization on bit planes was analyzed and the stability of Gray-code-based bit planes was proved. Furthermore, by calculating information entropy, the set of bit planes concluding the main contour information of images was determined. Finally, the procedure and algorithm for extracting effective contour information was described. The experimental results show that the proposed method can provide effective information for rough classification of images.

关键词： Graphic methods

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Kernel fitting for speech detection and enhancement

Kernel fitting for speech detection and enhancement

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International Conference on Signal processing Proceedings (ICSP)

作者： Benyong Liu Jing Zhang Xiang Liao Institute of Intelligent Information Processing / College of Computer Science and Information Technology Guizhou University Guiyang China Key Lab of Audio-Visual Material Examination Guizhou Public Security Department Guiyang 550001 China

A kernel fitting algorithm is proposed for speech denoising to improve the precision of voice activity detection (VAD) and the performance of speech enhancement, of some popular algorithms. In the algorithm, a noisy speech frame is filtered by kernel fitting, and then its power spectral density is estimated and weighted by a gain factor constructed from frame energy and zero-crossing rate, so that a speech signal is obviously discriminated from a nonspeech one. By incorporation of the VAD outputs and the noise effect into the kernel fitting process, a speech frame is enhanced with better performance than the spectra subtraction algorithm. Experiments are taken on a real life speech signal plus simulated noises, and the results show the potentiality of the proposed algorithms in speech detection and enhancement.

关键词： Speech Speech enhancement Kernel Fitting Noise measurement Noise

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Petri net model based specification and distributed control of robotic manufacturing systems

Petri net model based specification and distributed control ...

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International Conference on Information and Automation (ICIA)

作者： Gen'ichi Yasuda Bin Ge Department of Human and Computer Intelligence Nagasaki Institute of Applied Science Nagasaki Japan Liao Ning Key Lab of Intelligent Information Processing Economic & Technical Development Zone Dalian University of Technology Dalian China

ISBN: (纸本)9781424457014

The specification and distributed control of discrete event robotic manufacturing systems using Petri nets are considered, and a methodology of decomposition and coordination is presented for hierarchical and distributed control. First, a task specification is defined as a Petri net model at the conceptual level, and then transformed to the detailed Petri net representation of the subtasks. Finally, the overall Petri net is decomposed and the constituent subnets are assigned to local Petri net based controllers. The controllers are coordinated by the coordinator so that the decomposed transitions fire at the same time. System coordination algorithm through communication between the coordinator and the controllers, is presented. By the proposed method, modeling, simulation and control of large and complex manufacturing systems can be performed consistently using Petri nets.

关键词： Distributed control Manufacturing systems Petri nets Control systems Communication system control Intelligent robots Databases Flexible manufacturing systems Robotics and automation Competitive intelligence

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An analysis of the combination of global and local models for activity recognition in videos

An analysis of the combination of global and local models fo...

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Congress on Image and Signal processing, CISP

作者： Weiyao Lin Hongxiang Li Chunli Wang Wei Li Institute of Image Communication and Information Processing Department of Electronic Engineering Shanghai Jiaotong University Shanghai China Department of Electrical and Computer Engineering North Dakota State University Fargo ND USA School of Information Science & Technology Dalian Maritime University Dalian China School of Computer Science & Engineering Beihang University Beijing China

In this paper, we propose and analyze a framework of combining the global and local models for improving the activity recognition performance. Under the framework, several global-local-model combination methods are proposed for activity recognition. The advantages of combining the global and local models are also analyzed in detail. Experimental results demonstrate that the proposed framework can not only improve the recognition performance but also release the loads for parameter selection.

关键词： Hidden Markov models Solid modeling Videos Adaptation model Analytical models Accuracy Load modeling

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A method of region segmentation for motion blurred object in still images

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Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of technology 2010年第SUPPL. 2期42卷 114-117页

作者： Xiang, Lin Cui, Rong-Yi Intelligent Information Processing Lab Department of Computer Science and Technology Yanbian University Yanji 133002 China Department of Computing Science Huaiyin Institute of Technology Huaian 223003 China

In view of the problem of motion blurred region segmentation from clear background in still images, a segmenting method based on directional field and fuzzy membership was proposed in this paper. Firstly, motional region was located roughly according to the direction obtained from the directional field. Then, blurred region was segmented furthermore based on degree of membership calculated using fuzzy membership function, which was defined to measure the fuzzy degree of image. Finally, motion blurred region was segmented with morphological post processing. The experimental results show that the motion blurred region can be segmented more accurately by proposed method, which can meet the qualification of subsequent retrieving, recognizing and analyzing processing about motional objects.

关键词： Membership functions

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Multi-Variable Cost Function for Application Layer Multicast Routing

Multi-Variable Cost Function for Application Layer Multicast...

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2010 IEEE Global Telecommunications Conference GLOBECOM 2010

作者： Tien Anh Le Hang Nguyen Hongguang Zhang Department of Electrical and Computer Engineering University of Massachusetts Amherst Amherst USA National Science Center Kharkiv Institute of Physics and Technology” Kharkiv Ukraine Digital Signal Processing Indian Institute of Technology Delhi India National Academy of Science of Ukraine Scientific and Technological Center of Electrophysics Kharkiv Ukraine

Cost function is an essential part in Application Layer Multicast (ALM) routing algorithms. It is from a cost function that we can calculate links' costs and then build the data delivery tree for multicasting. Unfortunately, cost function remains an almost untouched research area in ALM routing. In this research, we propose a new multi-variable cost function considering various end-to-end QoS parameters simultaneously. The mathematical derivation process is also described in details so that one can apply it to obtain other multi-variable cost functions according to their specific requirements. The newly proposed multi-variable cost function can avoid congestion before it happens, preventing the data delivery tree from being frequently or unnecessarily changed while still be adaptable to the dynamic requirements of different applications. With theoretical analysis, we have proved that the new cost function can provide better performance for ALM routing algorithms compared to conventional cost functions.

关键词： Cost function Bandwidth Delay Quality of service Routing Equations IEEE Communications Society

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The method of image restoration in the environments of dust

The method of image restoration in the environments of dust

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IEEE International Conference on Mechatronics and Automation

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education TaiYuan University of Technology TaiYuan China College of Mechanical Engineering TaiYuan University of Technology TaiYuan China Institute for Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology WuHan China

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, a particle swarm optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with dual threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments.

关键词： Image edge detection Image restoration Degradation Atmospheric modeling Optical scattering Optical imaging

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Study on the Method of Image Restoration in the Environment of Dust

Study on the Method of Image Restoration in the Environment ...

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International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education Taiyuan University Of Technology Taiyuan China College of Mechanical Engineering Taiyuan University Of Technology Taiyuan China Institute of Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control HuaZhong University of Science and Technology Wuhan China

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, GA optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with automatic threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments.

关键词： Image edge detection Image restoration Scattering Degradation Gallium Atmospheric modeling Genetic algorithms

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A novel method of fingerprint minutiae extraction based on Gabor phase

A novel method of fingerprint minutiae extraction based on G...

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IEEE International Conference on Image processing

作者： Xin Gao Xiaoguang Chen Jia Cao Zirui Deng Chongjin Liu Jufu Feng Key Laboratory of Machine Perception MOE Department of Machine Intelligence School of Electronics Engineering and Computer Science Peking University Beijing China Institute of Image Processing and Pattern Recognition North-China University of Technology Beijing China

In this paper, a novel method of fingerprint minutiae extraction on grey-scale images is proposed based on the Gabor phase field. The novelty of our approach is that the proposed algorithm is performed on the transform domain, i.e. the Gabor phase field of the fingerprint image. This is different from most existing minutiae extraction methods, in which the minutiae are usually extracted from the binarized and thinned fingerprint image. Experimental results on benchmark data sets demonstrate that the proposed algorithm has promising performances.

关键词： Pixel Feature extraction Image quality Fingerprint recognition Detectors Frequency estimation Software algorithms

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A Discriminative Model for Traditional Mongolian Part of Speech

A Discriminative Model for Traditional Mongolian Part of Spe...

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Chinese Conference on Pattern Recognition (CCPR)

作者： Guanhong Zhang sloglo Odbal Department of Computer Science and Technology Key Laboratory of Network and Intelligent Information Processing Hefei University Hefei Anhui China Inner Mongolia University for the Nationalities Hohhot Inner Mongolia China Hefei Institutes of Physical Science Chinese Academy and Sciences Hefei Anhui China

This paper presents a discriminative model for part of speech tagging of traditional *** use Maximum Entropy Model with Morphological features of Mongolian. First, the context feature templates are defined and extracted from the training corpus. Then, the parameters of maximum entropy probability models are calculated. Experimental results show that integration of morphological features of Maximum Entropy Model for Mongolian part of speech tagging outperform HMM since they are flexible enough to capture many correlated non-independent features.

关键词： Hidden Markov models Speech Tagging Entropy Accuracy Natural languages Computational modeling

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