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IEEE International Conference on image processing

作者： Lei Wang Jiaji Wu Licheng Jiao Li Zhang Guangming Shi Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

A progressive image compression scheme is investigated using reversible integer discrete cosine transform (RDCT) which is derived from the matrix factorization theory. Previous techniques based on DCT suffer from bad performance in lossy image compression compared with wavelet image codec. And lossless compression methods such as IntDCT, I2I-DCT and so on could not compare with JPEG-LS or integer discrete wavelet transform (DWT) based codec. In this paper, lossy to lossless image compression can be implemented by our proposed scheme which consists of RDCT, coefficients reorganization, bit plane encoding, and reversible integer pre- and post-filters. Simulation results show that our method is competitive against JPEG-LS and JPEG2000 in lossless compression. Moreover, our method outperforms JPEG2000 (reversible 5/3 filter) for lossy compression, and the performance is even comparable with JPEG2000 which adopted irreversible 9/7 floating-point filter (9/7F filter).

关键词： image coding Discrete cosine transforms Transform coding Filters Performance loss Discrete wavelet transforms Codecs image reconstruction Laboratories Information processing

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Optimal Approximation of Linear Systems by an Improved Clonal Selection Algorithm

Optimal Approximation of Linear Systems by an Improved Clona...

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Congress on Evolutionary Computation

作者： Lining Zhang Maoguo Gong Licheng Jiao Jie Yang Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

Based on the theory of clonal selection in immunology, by introducing Baldwin effect, an improved clonal selection algorithm, termed as Baldwin clonal selection algorithm (BCSA), is proposed to solve the optimal approximation of linear systems. For engineering computing, the novel algorithm adopts three operations to evolve and improve the population: clonal proliferation operation, Baldwinian learning operation and clonal selection operation. The experimental study on the optimal approximation of a stable linear system and an unstable one show that the approximate models searched by the new algorithm have better performance indices than those obtained by some existing algorithms including the differential evolution algorithm, multi-agent genetic algorithm and artificial immune response algorithm.

关键词： Evolutionary computation

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Improved Clonal Selection Algorithm based on Lamarckian Local Search Technique

Improved Clonal Selection Algorithm based on Lamarckian Loca...

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Congress on Evolutionary Computation

作者： Jie Yang Maoguo Gong Licheng Jiao Lining Zhang Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

In this paper, we introduce Lamarckian learning theory into the clonal selection algorithm and propose a sort of Lamarckian clonal selection algorithm, termed as LCSA. The major aim is to utilize effectively the information of each individual to reinforce the exploitation with the help of Lamarckian local search. Recombination operator and tournament selection operator are incorporated into LCSA to further enhance the ability of global exploration. We compared LCSA with the clonal selection algorithm (CSA) in solving twenty benchmark problems to test the performance of LCSA. The results demonstrate that LCSA is effective and efficient in solving numerical optimization problems.

关键词： Artificial neural networks Immune system Cloning Optimization Evolutionary computation Benchmark testing Interpolation

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Artificial immune network clustering algorithm based on support vector domain description

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Journal of Computational Information Systems 2008年第4期4卷 1483-1488页

作者： Huang, Wenlong Jiao, Licheng Jia, Jian Key Laboratory of Intelligent Perception and Image Understanding Institute of Intelligent Information Processing Xidian University Xi'an 710071 China Troops No.95948 of PLA Lanzhou 732750 China

This paper aims at the combination of the artificial immune network and the support vector domain description for clustering. A new artificial immune antibody network is proposed. In the network, the antibody neighborhood is represented as a support vector hypersphere, and an adaptive learning coefficient is presented. The input data set is firstly divided into subsets by antibodies, then each subset is mapped into a hypersphere respectively in a high dimensional feature space by support vector domain description. Finally the clustering results of the local support vector hyperspheres are combined to yield a global clustering solution by the minimal spanning tree, which need not a predefined number of clustering. The experimental results with several data sets illustrate the effectiveness of the proposed algorithm.

关键词： Antibodies

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A Particle Filtering Algorithm for Tracking Moving Target under Clutter

A Particle Filtering Algorithm for Tracking Moving Target un...

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7th World Congress on intelligent Control and Automation (WCICA 2008), vol.13

作者： Guocheng Liu Yongji Wang Chinese Education Ministry Key Laboratory for Image Processing & Intelligent Control Huazhong University of Science and Technology Wuhan China

On visual tracking, a particle filter algorithm was presented to track a moving target under clutter environment which can deal with rotation, scale changes, variations in the light source and partial occlusions. So it can track the target with robustness. The proposed method was based on particle filter, integrated with color histogram in the measurement model, and the system model was second order autoregressive process. The algorithm took into account the latest observations and the tracked target can be rigid or non-rigid. Also the method can run in real-time. The experimental results confirm that the method is effective even when the monocular camera is moving and the target object is partially occluded in a clutter background.

关键词： Particle filter Visual tracking Color histogram

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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 (WCICA 2008), vol.10

作者： Xiaoping Wang Huan Qi Henghui Xiao Xiaopan Zhang Key Laboratory of Image Processing and Intelligent Control Institute of Systems Engineering Huazhong University of Science and Technology Wuhan China

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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Development and Application of a Sliding Mode based Diagonal Recurrent Cerebellar Model Articulation Controller

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IFAC Proceedings Volumes 2008年第2期41卷 5986-5991页

作者： Shan Liu Yongji Wang Qi Xu Huijuan Fang Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China Tel: 86-27-87557284

This paper presents a sliding-mode-based diagonal recurrent cerebellar model articulation controller (SDRCMAC) for multiple-input-multiple-output (MIMO) uncertain nonlinear systems. Sliding mode technology is used to reduce the dimension of the control system. Two learning stages are adopted to train the SDRCMAC and to improve the stability of the control system. Lyapunov stability theorem and Barbalat's lemma are adopted to guarantee the asymptotical stability of the system. Performance is illustrated on a two-link robotic control and motor control of the human arm in the sagittal plane.

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Unsupervised texture image segmentation using multiobjective evolutionary clustering ensemble algorithm

Unsupervised texture image segmentation using multiobjective...

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Congress on Evolutionary Computation

作者： Xiaoxue Qian Xiangrong Zhang Licheng Jiao Wenping Ma Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Institute of Intelligence Information Processing Xidian University Xi'an China

Multiobjective evolutionary clustering approach has been successfully utilized in data clustering. In this paper, we propose a novel unsupervised machine learning algorithm namely multiobjective evolutionary clustering ensemble algorithm (MECEA) to perform the texture image segmentation. MECEA comprises two main phases. In the first phase, MECEA uses a multiobjective evolutionary clustering algorithm to optimize two complementary clustering objectives: one based on compactness in the same cluster, and the other based on connectedness of different clusters. The output of the first phase is a set of Pareto solutions, which correspond to different tradeoffs between two clustering objectives, and different numbers of clusters. In the second phase, we make use of the meta-clustering algorithm (MCLA) to combine all the Pareto solutions to get the final segmentation. The segmentation results are evaluated by comparing with three known algorithms: K-means, fuzzy K-means (FCM), and evolutionary clustering algorithm (ECA). It is shown that MECEA is an adaptive clustering algorithm, which outperforms the three algorithms in the experiments we carried out.

关键词： Evolutionary computation

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Small universal spiking neural P systems with exhaustive use of rules

Small universal spiking neural P systems with exhaustive use...

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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Xingyi Zhang Yun Jiang Linqiang Pan Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hubei China

We consider the problem of looking for small universal spiking neural P systems with exhaustive use of rules, which was formulated as an open problem by Gheorghe Paun in a survey paper. Here, spiking neural P systems are used in two versions: as devices computing functions and as devices generating sets of numbers, with two ways of encoding the result of a computation. As devices of computing functions, if we associate the result with the distance between the first two spikes emitted by the output neuron, we produce a universal computing spiking neural P system with exhaustive use of rules (without delay) having 125 neurons; if we introduce the usual way of defining the result of a computation in membrane systems to encode the result, namely, the number of spikes emitted during a computation, then a universal computing system (without delay) with 126 neurons is also obtained in the sense of the exhaustive use of rules. For spiking neural P systems used as generators of sets of numbers, we construct a universal system (without delay) by using 128 neurons under the first way of defining the computation result, and a system (without delay) by using 127 neurons under the second way of defining the computation result.

关键词： Neurons Registers Tin Delay Generators Distance measurement Biomembranes

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Neutrosophic combination rules based on dempster-shafer theory and Dezert-Smarandache theory

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Information Technology Journal 2008年第7期7卷 1023-1029页

作者： Gao, Jian Huang, Xinhan Wang, Min Li, Xinde Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of CSE HUST Wuhan 430074 China School of Automation Southeast University Nanjing 210096 China

Several neutrosophic combination rules based on the Dempster-Shafer theory (DST) and Dezert-Smarandache theory (DSmT) are presented in this study. The new information fusing approaches proposed the neutrosophic belief assignment to represent the evidences and connect the DST and DSmT with neutrosophic theory. Neutrosophic theory used the components truth, indeterminacy and falsity to represent any idea, which provides a better approach to express the real world. The DST-based and DSmT-based combination rules can fuse information more effectively. The new combination rules utilized the advantages of DST, DSmT and neutrosophic theory. They are more adapted to describing the human mind and helping to make correct decisions. To fuse the information expressed in natural language, the qualitative neutrosophic combination rules of information have been proposed in this study too. Some application examples have been given to support the proposed combination rules. Compared with the original DST-based and DSmT-based combination rules, the neutrosophic combination rules can provide more useful information and have wider application field. © 2008 Asian Network for Scientific Information.

关键词： Information fusion

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