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MULTI-ROBOT TRACKING OF MOBILE TARGET BASED ON COMMUNICATION

IFAC Proceedings Volumes 2008年第2期41卷 10397-10402页

作者： Lei Liu Yongji Wang Dept. of Control Science and Engineering Huazhong Univ. of Sci. and Tech. Wuhan Hubei China 430074 Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan Hubei China 430074

Multi-robot tracking of mobile target is studied in the paper, which is based on the communication and sensors. For an independent tracking robot, the processes are separated into three layers and four tasks, and allocated to different robots for distinct roles in tracking, which is named the Distributed Decision control System (DDCS). After that, two tracking models, centralized and distributed models, are designed for multi-robot tracking. Furthermore, a Proportional Navigation Guidance Law (PNGL) and l-ϕ formation control algorithm are mentioned to realize the robot motion control. At last the simulation has shown the feasibility and validity of both models.

关键词： Multi-robot tracking DDCS PNGL Communication based l-ϕ formation control algorithm

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Feature fusion as a practical solution toward noncooperative iris recognition

Feature fusion as a practical solution toward noncooperative...

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11th International Conference on Information Fusion, FUSION 2008

作者： Tajbakhsh, Nima Araabi, Babak N. Soltanianzadeh, Hamid Control and Intelligent Processing Center of Excellence School of Electrical and Computer Eng. University of Tehran Tehran Iran School of Cognitive Sciences IPM Tehran Iran Image Analysis Lab. Radiology Dept. Henry Ford Health System Detroit MI 48202 United States

ISBN: (纸本)9783000248832

In noncooperative Iris recognition one should deal with uncontrolled behavior of the subject as well as uncontrolled lighting conditions. That means imperfect focus, contrast, brightness, and orientation among the others. To cope with this situation we propose to take iris images at both near infrared (NIR) and visible light (VL) and use them simultaneously for recognition. In this paper, a novel approach for iris recognition is proposed so that extracted features of NIR and VL images are fused to improve the recognition rate. When the images do not have enough quality due to focus, contrast, etc., effects of feature fusion is more pronounced. This is the situation in UTIRIS database, which is used in our experiments. Experimental results show that the proposed approach, especially in small training samples, leads to a remarkable improvement on recognition rate compared with either NIR or VL recognition.

关键词： Biometrics

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An intelligent decision combiner applied to noncooperative iris recognition

An intelligent decision combiner applied to noncooperative i...

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11th International Conference on Information Fusion, FUSION 2008

ISBN: (纸本)9783000248832

In despite of successful implementation of iris recognition systems, noncooperative recognition is still remained as an unsolved problem. Unexpected behavior of the subjects and uncontrolled lighting conditions as the main aspects of noncooperative iris recognition result in blurred and noisy captured images. This issue can degrade the performance of iris recognition system. In this paper, to address the aforementioned challenges, an intelligent decision combiner is proposed in which prior to perform decision fusion;an automatic image quality inspection is carried out. The goal is to determine whether captured decisions based on visible light (VL) and near infrared (NIR) images have enough reliability to incorporate into final decision making. Experimental results on the UTIRIS confirm the superior performance of the proposed combiner in comparison with other common nontrainable decision combiners whereas in all cases, the effectiveness of fusion approach makes it a reliable solution to noncooperative subjects' behavior and uncontrolled lighting conditions.

关键词： Decision making

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Method of boundary extraction based on schrödinger equation 21

Method of boundary extraction based on schrödinger equation

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2008 21st ISPRS International Congress for Photogrammetry and Remote Sensing

作者： Lou, Liantang Zhan, Xin Fu, Zhongliang Ding, Mingyue School of Remote Sensing and Information Engineering Wuhan University Wuhan430072 China School of Science Wuhan Institute of Technology Wuhan430073 China Institute for Pattern Recognition and Artificial Intelligence Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan430074 China

To overcome the main drawbacks of global minimal for active contour models (L. D. Cohen and Ron Kimmel) that the contour is only extracted partially for low SNR images, Method of boundary extraction based on Schrödinger Equation is proposed. Our Method is based on computing the numerical solutions of initial value problem for second order nonlinear Schrödinger equation by using discrete Fourier Transformation. Schrödinger transformation of image is first given. We compute the probability P(b,a) that a particle moves from a point a to another point b according to I-Type Schrödinger transformation of image and obtain boundary of object by using quantum contour model.

关键词： Initial value problems

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A no-reference ringing metrics for images deconvolution

A no-reference ringing metrics for images deconvolution

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International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

作者： Bo-Xin Zuo Jin-Wen Tian De-Lie Ming State Key Laboratory of Education Commission for Image Processing and Intelligent Control Institute For Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

In this paper, we presented a ringing metric to evaluate the quality of images restored using iterative image restoration algorithms. A ringing metrics is used to assessment the restored images based on the Gabor filter. The experimental results validate the proposed method perform well over a wide range of restoration image ringing levels assessment. And the proposed model has given good agreement with observer ratings obtained in subjective experiments.

关键词： image restoration Gabor filters image edge detection Oscillators Deconvolution Maximum likelihood detection Band pass filters

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Co-scheduling model and algorithm of the three gorges-gezhou dam based on GA

Co-scheduling model and algorithm of the three gorges-gezhou...

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7th World Congress on intelligent control and Automation

作者： Wang, Xiaoping Qi, Huan Xiao, Henghui Zhang, Xiaopan Huazhong Univ Sci & Technol Inst Syst Engn Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

ISBN: (纸本)9781424421138

This paper provided a mathematic model for Three Gorges-Gezhou dam co-scheduling problems, based on full analysis of Three Gorges-Gezhou dam's actual needs, to maximize the total throughput of Three Gorges-Gezhou dam, to maximize the utilization ratio of shiplock area and minimize the total navigation shiplock waiting time under eight constraint conditions. Then a scheduling algorithm based on GA was pointed out. The three gorges south lock, Gezhou dam lock, the three gorges north lock were optimization searched separately in the GA algorithm. The scheduling results of the three gorges south lock were taken as the origin of the whole plan period, and also were taken as the basis of the Gezhou dam scheduling together with the ship applied information. The scheduling results of Gezhou dam were regarded as the basis of the three gorges north lock scheduling together with the ship applied information, so repeated, until the optimal scheduling results were given, or the most iterative step was reached. The applied result shows that making a period plan of two dam five lock only needs 2 minutes, and the plan is quite effective according to practical application.

关键词： genetic algorithm the three gorges-gezhou dam co-scheduling mathematical model

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The Application of A Novel Target Region Extraction Model Based on Object-Accumulated Visual Attention Mechanism

The Application of A Novel Target Region Extraction Model Ba...

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International Conference on Natural Computation (ICNC)

作者： Jie Xiao Chao Cai Mingyue Ding Chengping Zhou Institute of Pattern Recognition and Artificial Intelligence State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

Combining bottom-up and top-down attention influences, a novel region extraction model which based on object-accumulated visual attention mechanism is proposed in this paper. Compared with early research, the new approach brings in prior information at the proper time, updates scan path dynamically, needs less computational resources and reduces the probability to direct the attention to a less-meaning area. The application to search an airport target in remote sensing image was provided, through which the novel mechanism that how visual attention chose the area was described. Compared with another two region extraction models, experimental results confirm the effectiveness of the approach proposed in this paper.

关键词： Data mining Object detection Computer applications Chaos Pattern recognition Artificial intelligence laboratories image processing intelligent control Airports

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An Improved Shuffled Frog Leaping Algorithm with Cognitive Behavior

An Improved Shuffled Frog Leaping Algorithm with Cognitive B...

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7th World Congress on intelligent control and Automation

作者： Zhang, Xuncai Hu, Xuemei Cui, Guangzhao Wang, Yanfeng Niu, Ying Huazhong Univ Sci & Technol Dept Control Sci & Engn Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Zhengzhou Univ Light Ind Coll Elect & Elect Engn Zhengzhou 450002 Peoples R China Henan Polytechn Inst Henan Dept Elect Engn Jiaozuo 473009 Peoples R China

ISBN: (纸本)9781424421138

Shuffled frog leaping (SFL) is a population based, cooperative search metaphor inspired by natural memetics. Its ability of adapting to dynamic environment makes SFL become one of the most important memetic algorithms. In order to improve the algorithm's stability and the ability to search the global optimum, a novel 'cognition component' is introduced to enhance the effectiveness of the SFL namely frog not only adjust its position according to the best individual within the memeplex or the global best of population but also according to thinking of the frog itself. To validate the improved SFL (ISFL) method, numerous simulations were conducted to compare SFL and ISFL using six benchmark problems for continuous and discrete optimization. According to the simulation results, adding the cognitive behavior to SFL significantly enhances the performance of SFL in solving the optimization problems, and the improvements are more evident with the scale of the problem increasing.

关键词： Shuffled frog leaping Particle swarm optimization Memetic algorithms Cognitive behavior

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Data Fusion and Efficient Algorithm for Moving Target Tracking

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IFAC Proceedings Volumes 2008年第2期41卷 2406-2411页

作者： Guocheng Liu Yongji Wang Chinese Education Ministry Key Lab. for Image Processing and Intelligence Control Department of Control Science and Engineering Huazhong University of Science and Technology P.R. China (Tel: 0086-27-68772267

The principle of target tracking and data fusion techniques are discussed. To resolve high uncertainty that exists in sensors of mobile robots, one multi-sensor data fusion algorithm is presented. The algorithm is based on particle filter techniques, fuses the information coming from multiple sensors and merges different state space models. So it can be used to eliminate system and measurement noise and estimate value of position and headings of mobile robot. On simulation experiments, we compare different cases such as single sensors and multi-sensor data fusion, the results demonstrate the feasibility and effectiveness of this algorithm and exhibits good tracking performance.

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Dim small targets fusion detection in infrared image

Dim small targets fusion detection in infrared image

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Yu-Qiu Sun Yu Zheng Jin-Wen Tian Jian Liu School of Information and Mathematics Yangtze University Jingzhou China State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China State Education Commission Key Laboratory for Image Processing and Intelligent Control Department of Electronic Information and Enginery of Huazhong University of Science and Technology Wuhan China

To infrared images, the contrast of target and background is low, dim small targets have no concrete shapes and their textures cannot be reliable predicted. The paper puts forward a novel algorithm to fuse mid-wave and long-wave infrared images and detect targets. Firstly, the source images are decomposed by wavelet transformation. In usual, targets in infrared images are man-made, and their fractal dimension is different comparing with natural background. In wavelet transformation domain high-frequency part, we calculate local fractal dimension and set up fusion rule to merge corresponding sub-images of two matching source images. In low-frequency, we extract local maximum gray level to fuse them. Then reconstruct image by wavelet inverse transformation and obtain fused result image. In fusion results, the contrast between targets and background has obvious changes. And targets can be detected using contrast threshold. The experimental results show that the method proposed in this paper using wavelet transformation fractal dimension to fuse dual band infrared images, and then detect targets is better than using mid-wave or long -wave infrared images detect targets alone.

关键词： Fractals Wavelet transforms Pixel Object detection Fuses Approximation methods Manganese

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