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International Conference on image Analysis and Signal processing, IASP

作者： Kexiang Liu Jie Qian Ruike Yang School of science Xidian University Xi'an China

A new type of real-time image stabilization system is introduced in present paper. RANSAC Algorithm is used in the system. The accuracy and speed of image stabilization is improved effectively. A low-cost and high-performance solution of real-time digital image stabilization system is given in this paper. Video stabilization working principle is discussed and the moving image mathematical model is set up. The RANSAC Algorithm can reduce the amount of calculation and the error rate of block matching. Simulation of the real-time image stabilization system is accomplished. The result shows the new model is effective; the power SNR of the video is raised about 8-10 dB.

关键词： Motion estimation Partitioning algorithms Digital images Real time systems Error analysis Motion compensation Mathematical model Power system modeling Digital signal processing US Department of Transportation

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A Fruit Size Detecting and Grading System Based on image processing

A Fruit Size Detecting and Grading System Based on Image Pro...

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2010 Second International Conference on Intelligent Human-Machine systems and Cybernetics(第二届智能人机系统与控制论国际学术会议 IHMSC 2010)

作者： Hongshe Dang Jinguo Song Qin Guo School of Electric and Information Engineering Shaanxi University of Science and Technology Xi'an CityShaanxi710021 China

this paper presents a fruit size detecting and grading system based on image processing. After capturing the fruit side view image, some fruit characters is extracted by using detecting algorithms. According to these characters, grading is realized. Experiments show that this embedded grading system has the advantage of high accuracy of grading, high speed and low cost. It will have a good prospect of application in fruit quality detecting and grading areas.

关键词： embedded system size detecting fruit grading image processing

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An Iterative Surface Evolution Algorithm for Multiview Stereo

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EURASIP JOURNAL ON image AND VIDEO processing 2010年第unknown期2010卷 274269-274269页

作者： xi, Yongjian Duan, Ye Univ Missouri Dept Comp Sci Columbia MO 65211 USA

We propose a new iterative surface evolution algorithm for multiview stereo. Starting from an embedding space such as the visual hull, we will first conduct robust 3D depth estimation (represented as 3D points) based on image correlation. A fast implicit distance function-based region growing method is then employed to extract an initial shape estimation based on these 3D points. Next, an explicit surface evolution will be conducted to recover the finer geometry details of the recovered shape. The recovered shape will be further improved by several iterations between depth estimation and shape reconstruction, similar to the Expectation Maximization (EM) approach. The experiments on the benchmark datasets show that our algorithm can obtain high-quality reconstruction results that are comparable with the state-of-art methods, with considerable less computational time and complexity.

关键词： image processing THREE-dimensional imaging COMPUTER algorithms ITERATIVE methods (Mathematics) EVOLUTIONARY computation EMBEDDED computer systems image quality analysis image reconstruction

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Feature extraction of hyperspectral images based on preserving neighborhood discriminant embedding

Feature extraction of hyperspectral images based on preservi...

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International Conference on image Analysis and Signal processing, IASP

作者： Jinhuan Wen Zheng Tian Hongwei She Weidong Yan School of Science Northwestern Polytechnical University Xi'an China State Key Laboratory of Remote Sensing Science Institute of Remote Sensing Applications Chinese Academy and Sciences Beijing China

A novel manifold learning feature extraction approach-preserving neighborhood discriminant embedding (PNDE) of hyperspectral image is proposed in this paper. The local geometrical and discriminant structure of the data manifold can be accurately characterized by within-class neighboring graph and between-class neighboring graph. Unlike manifold learning, such as LLE, Isomap and LE, which cannot deal with new test samples and images larger than 70×70, the method here can process full scene hyperspectral images. Experiments results on hyperspectral datasets and real-word datasets show that the proposed method can efficiently reduce the dimensionality while maintaining high classification accuracy. In addition, only a small amount of training samples are needed.

关键词： Feature extraction Hyperspectral imaging Hyperspectral sensors Remote sensing Testing Clustering algorithms Layout Data mining Principal component analysis Learning systems

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Realization and Optimization of Face Detection Algorithm Based on DSP

Realization and Optimization of Face Detection Algorithm Bas...

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International Conference of Information Science and Management Engineering (ISME)

作者： Ling-bin Kong Jin-ye Peng Zhao-qiang xia Yu Lian Shao-chong Fan Dept. of Electron. & Inf. Northwestern Polytech. Univ. Xi'an China

It introduced the principle and the process of human face detection algorithm, as well as its implementation and optimization using DSP. It applied AdaBoost algorithm to detect human face. Before the detection, some methods were used to optimize original image data, such as image scale, median filter, histogram equalization and edge detection. After the detection, it judged and modified the results to improve the detection accuracy further. Then it used many optimization methods to meet the real-time requirement. Experimental results show that, this DSP system can meet real-time requirement even if it detects faces in 720×576 high-resolution images, at the same time it has a high accuracy and low miss rate in a complex environment.

关键词： Face Digital signal processing Face detection Real time systems Classification algorithms Accuracy Pixel

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The creation of a hue-constancy space for color management system

The creation of a hue-constancy space for color management s...

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International Conference on Computer Application and System Modeling (ICCASM)

作者： Xue-mei Luo Yi-feng Wang Hai-hong Zheng Institute of Computer Peripherals Xidian University Xi'an China

The CIELAB space is known as hue nonconstancy. This is why gamut mapping in constant hue angle in CIELAB space may not give satisfactory performances. To solve this problem, a new color space tLAB was constructed, which is used to replace CIELAB in color management system. Firstly, the hue in CIELAB is corrected according to Munsell renotation data, and the hue-constancy tLAB color space is created. Then 3D look up table is used to characterize the nonlinear relationship between CIELAB and tLAB. Finally, an implementation scheme for color management with a low spatio-temporal cost is presented. Experiments show that the results of gamut mapping in the new tLAB space gain an advantage over the traditional ones. In addition, the color management using tLAB color space has real time performance and universality.

关键词： image color analysis systems modeling Computer applications Signal processing algorithms Printers Extraterrestrial measurements Color

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Clonal Selection Classification Algorithm for High-Dimensional Data

Clonal Selection Classification Algorithm for High-Dimension...

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2010 International Conference on Life System Modeling and Simulation & 2010 International Conference on Intelligent Computing for Sustainable Energy and Environment

作者： Ruochen Liu, Ping Zhang, Licheng Jiao Key Laboratory of Intelligent Perception and image Understanding of Ministry of Education of China, Institute of Intelligent Information processing, xidian University, xi’an, 710071

Many important problems involve classifying high-dimensional data sets, which is very difficult because learning methods suffer from the curse of dimensionality. In this paper, Clonal Selection Classification Algorithm is proposed for high-dimensional data. First, an automatic non-parameter uncorrelated discriminant analysis (UDA) is adopted for dimensionality reduction (DR). Due to the favorable global search and local search, Clonal Selection Algorithm (CSA) is used to design classifier. The proposed method has been extensively compared with nearest neighbor (NN) based on Principal Component Analysis and linear discrimination analysis (PCA+LDA), nearest neighbor (NN) based on UDA (UDA+NN) and FCM based on UDA (FCM+UDA) when classifying six UCI data sets and a SAR image classification problems. The results of experiment indicate the superiority of the proposed algorithm over the three other classification algorithms in term of classification accuracy and stability.

关键词： dimensionality reduction, UDA, Clonal Selection Algorithm (CSA), SAR image classification

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Particle Swarm Optimization based Clustering:A Comparison of Different Cluster Validity Indices

Particle Swarm Optimization based Clustering:A Comparison of...

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2010 International Conference on Life System Modeling and Simulation & 2010 International Conference on Intelligent Computing for Sustainable Energy and Environment

作者： Ruochen Liu, xiaojuan Sun, Licheng Jiao Key Laboratory of Intelligent Perception and image Understanding of Ministry of Education of China, Institute of Intelligent Information processing, xidian University, xi’an, 710071

Most of clustering algorithms based on natural computation aim to find the proper partition of data to be processed by optimizing certain criteria, so-called as cluster validity index, which must be effective and can reflect a similarity measure among objects properly. Up to now, four typical cluster validity indices such as Euclid distance-based PBM index, the kernel function induced CS measure, Point Symmetry (PS) distance-based index, Manifold Distance (MD) induced index have been proposed. But, there is not a detailed comparison among these indexes. In this paper, we design a particle swarm optimization based clustering algorithm, in which, four different cluster validity index above mentioned are used as the fitness of a particle respectively. By applying the proposed algorithm to a number of artificial synthesized data and UCI data, the performance of different validity indices are compared in terms of clustering accuracy and robustness at length.

关键词： particle swarm optimization, clustering, cluster validity, PBM index, CS measure, point symmetry distance, manifold distance

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Immune secondary response and clonal selection inspired optimizers

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Progress in Natural Science:Materials International 2009年第2期19卷 237-253页

作者： Maoguo Gong a,Licheng Jiao a,Lining Zhang a,Haifeng Du b a Key Laboratory of Intelligent Perception and image Understanding of Ministry of Education of China,Institute of Intelligent Information processing,xidian University,xi’an 710071,China b School of Public Policy and Administration,xi’an Jiaotong University,xi’an 710049,China [a]Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi’an 710071 China [b]School of Public Policy and Administration Xi’an Jiaotong University Xi’an 710049 China

The immune system’s ability to adapt its B cells to new types of antigen is powered by processes known as clonal selection and affinity maturation. When the body is exposed to the same antigen,immune system usually calls for a more rapid and larger response to the antigen,where B cells have the function of negative adjustment. Based on the clonal selection theory and the dynamic process of immune response,two novel artificial immune system algorithms,secondary response clonal programming algorithm (SRCPA) and secondary response clonal multi-objective algorithm (SRCMOA),are presented for solving single and multi-objective optimization problems,respectively. Clonal selection operator (CSO) and secondary response operator (SRO) are the main operators of SRCPA and SRCMOA. Inspired by the clonal selection theory,CSO reproduces individuals and selects their improved maturated progenies after the affinity mat-uration process. SRO copies certain antibodies to a secondary pool,whose members do not participate in CSO,but these antibodies could be activated by some external stimulations. The update of the secondary pool pays more attention to maintain the population diversity. On the one hand,decimal-string representation makes SRCPA more suitable for solving high-dimensional function optimiza-tion problems. Special mutation and recombination methods are adopted in SRCPA to simulate the somatic mutation and receptor edit-ing process. Compared with some existing evolutionary algorithms,such as OGA/Q,IEA,IMCPA,BGA and AEA,SRCPA is shown to be able to solve complex optimization problems,such as high-dimensional function optimizations,with better performance. On the other hand,SRCMOA combines the Pareto-strength based fitness assignment strategy,CSO and SRO to solve multi-objective optimization problems. The performance comparison between SRCMOA,NSGA-Ⅱ,SPEA,and PAES based on eight well-known test problems shows that SRCMOA has better performance in converging to approximate Pareto

关键词： Clonal selection Secondary response Artificial immune systems Evolutionary algorithms

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Detecting and tracking humans using a man-portable robot

Detecting and tracking humans using a man-portable robot

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Conference on Unmanned systems Technology xi

作者： Baran, David Fung, Nick Ho, Sean Sherman, James USA Res Lab Adelphi MD 20783 USA

ISBN: (纸本)9780819475985

Large gains in the automation of human detection and tracking techniques have been made over the past several years. Several of these techniques have been implemented on larger robotic platforms, in order to increase the situational awareness provided by the platform. Further integration onto a smaller robotic platform that already has obstacle detection and avoidance capabilities would allow these algorithms to be utilized in scenarios that are not plausible for larger platforms, such as entering a building and surveying a room for human occupation with limited operator intervention. However, transitioning these algorithms to a man-portable robot imparts several unique constraints, including limited power availability, size and weight restrictions, and limited processor ability. Many imaging sensors, processing hardware, and algorithms fail to adequately address one or more of these constraints. In this paper, we describe the design of a payload suitable for our chosen man-portable robot, the iRobot Packbot. While the described payload was built for a Packbot, it was carefully designed in order to be platform agnostic, so that it can be used on any man-portable robot. Implementations of several existing motion and face detection algorithms that have been chosen for testing on this payload are also discussed in some detail.

关键词： human detection human tracking Packbot image processing man-portable

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