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2016 IEEE Chinese Guidance, Navigation and Control Conference (IEEE CGNCC2016)

作者： Chi Yuan Khaled A.Ghamry Zhixiang Liu Youmin Zhang Department of Mechanical and Industrial Engineering Concordia University IEEE Department of Information and Control Engineering Xi'an University of Technology

ISBN: (纸本)9781467383196

Early forest fire alarm systems are critical in making prompt response in the event of unexpected *** cameras,improvements in memory,and enhanced computation power have all enabled the design and real-time application of fire detecting algorithms using light and smallsize embedded surveillance *** is vital in situations where the performance of traditional forest fire monitoring and detection techniques are *** paper presents a forest fire monitoring and detection method with visual sensors onboard unmanned aerial vehicle(UAV).Both color and motion features of fire are adopted for the design of the studied forest fire detection *** is for the purpose of improving fire detection performance,while reducing false alarm *** experiments are conducted to demonstrate the effectiveness of the studied forest fire detection methodologies.

关键词： UAV red image Unmanned Aerial Vehicle Based Forest Fire Monitoring and Detection Using image processing Technique

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图像场景语义分类研究进展综述

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系统工程与电子技术 2016年第4期38卷 936-948页

作者：顾广华韩晰瑛陈春霞赵耀燕山大学信息科学与工程学院河北秦皇岛066004 北京交通大学信息科学研究所北京100044

场景语义分类是图像理解领域中一个重要的研究方向,涉及到信号处理、模式识别、计算机视觉和认知科学等多学科交叉。场景分类任务中,图像内容描述和分类判决是两大关键问题。图像内容描述力图得到关于场景图像最具判别意义的表示,而分... 详细信息

场景语义分类是图像理解领域中一个重要的研究方向,涉及到信号处理、模式识别、计算机视觉和认知科学等多学科交叉。场景分类任务中,图像内容描述和分类判决是两大关键问题。图像内容描述力图得到关于场景图像最具判别意义的表示,而分类判决则对训练样本集的图像内容描述学习、训练,并建模得到某类场景图像区别于其他场景类图像的计算模型。目前,很多场景分类方法针对图像内容描述和图像分类进行了深入的研究,对室外人造场景、室外自然场景和室内场景图像进行分类,取得了较好的分类效果。然而,场景图像自身内容上的变化和差异,既会造成同一场景类内对象的差异性,同时也造成不同场景类之间图像的视觉相似性,特别是对于不同的室内场景类。因此,场景语义分类任务十分困难,是计算机视觉和认知心理学领域中一个颇具挑战性的难题。室外图像场景分类研究相对成熟,而室内图像场景分类研究却进展缓慢。本文综述了图像场景语义分类的研究进展,并分析了场景分类算法的性能,指出场景语义分类研究中存在的问题。

关键词：场景语义分类特征提取图像描述主题模型分类器设计

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A high-precision instrument for analyzing nonlinear dynamic behavior of bearing cage

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REVIEW OF SCIENTIFIC INSTRUMENTS 2016年第8期87卷 085105-085105页

作者： Yang, Z. Chen, H. Yu, T. Li, B. Northwestern Polytech Univ Sch Aeronaut Xian 710072 Peoples R China Xian Aerosp Prop Inst Xian 710100 Peoples R China Xi An Jiao Tong Univ State Key Lab Mfg & Syst Engn Xian 710054 Peoples R China

The high-precision ball bearing is fundamental to the performance of complex mechanical systems. As the speed increases, the cage behavior becomes a key factor in influencing the bearing performance, especially life and reliability. This paper develops a high-precision instrument for analyzing nonlinear dynamic behavior of the bearing cage. The trajectory of the rotational center and non-repetitive run-out( NRRO) of the cage are used to evaluate the instability of cage motion. This instrument applied an aerostatic spindle to support and spin test the bearing to decrease the influence of system error. Then, a high-speed camera is used to capture images when the bearing works at high speeds. A 3D trajectory tracking software TEMA Motion is used to track the spot which marked the cage surface. Finally, by developing the MATLAB program, a Lissajous' figure was used to evaluate the nonlinear dynamic behavior of the cage with different speeds. The trajectory of rotational center and NRRO of the cage with various speeds are analyzed. The results can be used to predict the initial failure and optimize cage structural parameters. In addition, the repeatability precision of instrument is also validated. In the future, the motorized spindle will be applied to increase testing speed and image processing algorithms will be developed to analyze the trajectory of the cage. Published by AIP Publishing.

关键词： Cameras Kinematics Testing procedures image motion analysis Movement sensors

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一种基二快速Hadamard变换的并行算法

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信息与控制 2016年第6期45卷 707-712,721页

作者：秦书嘉缪磊崔龙席宁中国科学院沈阳自动化研究所辽宁沈阳110016 中国科学院大学北京100049 密歇根州立大学

快速Hadamard变换被广泛应用于信号与图像处理、通信系统、数字逻辑等领域中.当问题规模非常大时,快速Hadamard变换有可能不能满足计算时间的要求;这种情况下,算法并行化是一种行之有效的手段.本文以单像素相机的压缩感知图像复原为应... 详细信息

快速Hadamard变换被广泛应用于信号与图像处理、通信系统、数字逻辑等领域中.当问题规模非常大时,快速Hadamard变换有可能不能满足计算时间的要求;这种情况下,算法并行化是一种行之有效的手段.本文以单像素相机的压缩感知图像复原为应用背景,利用基二快速Hadamard变换与快速傅里叶变换的结构相似性,提出一种通用的基二快速Hadamard变换的任务级并行算法,并用构造方式证明了该并行算法与串行算法计算结果之间的等价性.仿真表明对于小于2^(20)向量长度的问题规模以及并行子任务数少于2^(10)的情况,该并行算法对比串行算法的数值计算结果的欧氏距离平方误差小于10^(-18),佐证了并行算法的正确性.在PC平台通过多核CPU上POSIX线程实现的实验表明:在该特定平台和特定配置上对于220至225向量长度的问题规模并行计算加速比为1.33~1.42,证明了文中提出方法的可行性和有效性.

关键词：单像素相机压缩感知 Hadamard变换并行算法

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Architecture-driven level set optimization: From clustering to subpixel image segmentation

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IEEE Transactions on Cybernetics 2015年第99期PP卷 3181-3194页

作者： Balla-Arabé, Souleymane Gao, xinbo Ginhac, Dominique Brost, Vincent Yang, Fan Laboratory of Electronic Computing and Imaging Sciences CNRS-UMR 6306 University of Burgundy Dijon21078 France State Key Laboratory of Integrated Services Networks School of Electronic Engineering Xidian University Xi'an710071 China

Thanks to their effectiveness, active contour models (ACMs) are of great interest for computer vision scientists. The level set methods (LSMs) refer to the class of geometric active contours. Comparing with the other ACMs, in addition to subpixel accuracy, it has the intrinsic ability to automatically handle topological changes. Nevertheless, the LSMs are computationally expensive. A solution for their time consumption problem can be hardware acceleration using some massively parallel devices such as graphics processing units (GPUs). But the question is: which accuracy can we reach while still maintaining an adequate algorithm to massively parallel architecture? In this paper, we attempt to push back the compromise between, speed and accuracy, efficiency and effectiveness, to a higher level, comparing with state-of-the-art methods. To this end, we designed a novel architecture-aware hybrid central processing unit (CPU)- GPU LSM for image segmentation. The initialization step, using the well-known k-means algorithm, is fast although executed on a CPU, while the evolution equation of the active contour is inherently local and therefore suitable for GPU-based acceleration. The incorporation of local statistics in the level set evolution allowed our model to detect new boundaries which are not extracted by the used clustering algorithm. Comparing with some cutting-edge LSMs, the introduced model is faster, more accurate, less subject to giving local minima, and therefore suitable for automatic systems. Furthermore, it allows two-phase clustering algorithms to benefit from the numerous LSM advantages such as the ability to achieve robust and subpixel accurate segmentation results with smooth and closed contours. Intensive experiments demonstrate, objectively and subjectively, the good performance of the introduced framework both in terms of speed and accuracy. © 2015 IEEE.

关键词： Clustering algorithms

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Robust Clutter Suppression and Moving Target Imaging Approach for Multichannel in Azimuth High-Resolution and Wide-Swath Synthetic Aperture Radar

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2015年第2期53卷 687-709页

作者： Zhang, Shuang-xi xing, Meng-Dao xia, xiang-Gen Guo, Rui Liu, Yan-Yang Bao, Zheng Xidian Univ Natl Key Lab Radar Signal Proc Xian 710071 Peoples R China Univ Delaware Dept Elect & Comp Engn Newark DE 19716 USA

This paper describes a clutter suppression approach and the corresponding moving target imaging algorithm for a multichannel in azimuth high-resolution and wide-swath (MC-HRWS) synthetic aperture radar (SAR) system. Incorporated with digital beamforming processing, MC-HRWS SAR systems are able to suppress the Doppler ambiguities to allow for HRWS SAR imaging and null the clutter directions to suppress clutter for ground moving target indication. In this paper, the degrees of freedom in azimuth for the multichannel SAR systems are employed to implement clutter suppression. First, the clutter and moving target echoes are transformed into the range compression and azimuth chirp Fourier transform frequency domain, i.e., coarse-focused images formation, when the clutter echoes are with azimuth Doppler ambiguity. Considering that moving targets are sparse in the imaging scene and that there is a difference between clutter and a moving target in the spatial domain, a series of spatial domain filters are constructed to extract moving target echoes. Then, using an extracted moving target echo, two groups of signals are formed, and slant-range velocity of a moving target can be estimated based on baseband Doppler centroid estimation algorithm and multilook cross-correlation Doppler centroid ambiguity number resolving approach. After the linear range cell migration correction and azimuth focus processing, a well-focused moving target image can be obtained. In addition, the proposed clutter suppression and imaging approach is not only adapted for uniformly displaced phase center sampling but also for the nonuniform sampling cases. Some simulation experiments are taken to demonstrate our proposed algorithms. Finally, some real measured data results are presented to validate the theoretical investigations and the proposed approaches.

关键词： Chirp Fourier transform (CFT) digital beamforming Doppler ambiguity Doppler centroid estimation ground moving target indication (GMTI) high resolution and wide swath

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Learning to Rank for Blind image Quality Assessment

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IEEE Transactions on Neural Networks and Learning systems 2015年第10期26卷 2275-2290页

作者： Gao, Fei Tao, Dacheng Gao, xinbo Li, Xuelong Video and Image Processing System Laboratory School of Electronic Engineering Xidian University Xi'an710071 China Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology 235 Jones Street Sydney UltimoNSW2007 Australia State Key Laboratory of Integrated Services Networks School of Electronic Engineering Xidian University Xi'an710071 China State Key Laboratory of Transient Optics and Photonics Xi'An Institute of Optics and Precision Mechanics Chinese Academy of Sciences Xi'an Shaanxi710119 China

Blind image quality assessment (BIQA) aims to predict perceptual image quality scores without access to reference images. State-of-the-art BIQA methods typically require subjects to score a large number of images to train a robust model. However, subjective quality scores are imprecise, biased, and inconsistent, and it is challenging to obtain a large-scale database, or to extend existing databases, because of the inconvenience of collecting images, training the subjects, conducting subjective experiments, and realigning human quality evaluations. To combat these limitations, this paper explores and exploits preference image pairs (PIPs) such as the quality of image Iais better than that of image Ibfor training a robust BIQA model. The preference label, representing the relative quality of two images, is generally precise and consistent, and is not sensitive to image content, distortion type, or subject identity;such PIPs can be generated at a very low cost. The proposed BIQA method is one of learning to rank. We first formulate the problem of learning the mapping from the image features to the preference label as one of classification. In particular, we investigate the utilization of a multiple kernel learning algorithm based on group lasso to provide a solution. A simple but effective strategy to estimate perceptual image quality scores is then presented. Experiments show that the proposed BIQA method is highly effective and achieves a performance comparable with that of state-of-the-art BIQA algorithms. Moreover, the proposed method can be easily extended to new distortion categories. © 2012 IEEE.

关键词： Learning algorithms

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Trans-PET: Towards Plug and Imaging Coincidence Measurement

Trans-PET: Towards Plug and Imaging Coincidence Measurement

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IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)

作者： Liu, Yuqing xi, Daoming Kao, Chien-Min Yuan, Rong Wang, Shuai Li, Chung-Yi Liang, xiao Li, Bingxuan Zhu, Jun Kim, Heejong xiao, Peng xie, Qingguo Wuhan Natl Lab Optoelect Wuhan Hubei Peoples R China Huazhong Univ Sci & Technol Biomed Engn Dept Wuhan Hubei Peoples R China Raycan Technol Co Ltd Suzhou Suzhou Jiangsu Peoples R China Univ Chicago Dept Radiol Chicago IL 60637 USA Chang Gung Univ Dept Elect Engn Taoyuan Taiwan

ISBN: (纸本)9781467398626

Recently, there is growing interest in directly digitizing the scintillation pulses in PET detectors. With digital pulse samples, in principle one can apply nontrivial signal analysis software algorithms to either yield better detection performance or more flexibility in detector design. Previously, we have proposed the MVT method for direct scintillation pulse sampling and developed several kinds of digital PET detectors named basic detector modules (BDM). These highly modular detectors output the resulting MVT samples in a uniform data format via a RJ45 connector while adopting the UDP protocol. For PET systems based on these detectors, single-event processing and coincidence filtering are all carried out by softwares. As a result, new processing/filtering methods can be readily updated or upgraded. Therefore, we wish to provide a BDM based design architecture to enable quick setup of a PET system. We use two system geometry definition files, named the SG file1 and SG file2, to define the types and number of the BDMs employed, as well as their positions and orientations. The MVT data processing like single event information retrieving, coincidence filtering, data format conversion, image reconstruction and data/image analysis are carried out by separate software modules with standard input and output definitions. Those software modules can be conveniently modified or replaced, and be put into cascade chains to provide desired functions. In this work, we present such a BDM based system design architecture, as well as the BDMs newly developed. As an example, a panel PET system adopting this architecture with 12 BDMs is shown with phantom imaging result.

关键词： Data handling

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Detection of Carious Lesions and Restorations Using Particle Swarm Optimization Algorithm

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INTERNATIONAL JOURNAL OF DENTISTRY 2016年第1期2016卷 3264545页

作者： Naebi, Mohammad Saberi, Eshaghali Fakour, Sirous Risbaf Naebi, Ahmad Tabatabaei, Somayeh Hosseini Moghadam, Somayeh Ansari Bozorgmehr, Elham Behnam, Nasim Davtalab Azimi, Hamidreza Zahedan Univ Med Sci Sch Dent Zahedan Iran Zahedan Univ Med Sci Sch Dent Dept Endodont Oral & Dent Dis Res Ctr Zahedan Iran Zahedan Univ Med Sci Dept Oral & Maxillofacial Surg Oral & Dent Dis Res Ctr Zahedan Iran Xi An Jiao Tong Univ Syst Inst State Key Lab Mfg Syst Engn Xian Peoples R China Zahedan Univ Med Sci Dept Operat Dent Oral & Dent Dis Res Ctr Zahedan Iran Zahedan Univ Med Sci Dept Periodontol Oral & Dent Dis Res Ctr Zahedan Iran Zahedan Univ Med Sci Dept Publ Hlth Oral & Dent Dis Res Ctr Zahedan Iran Tabriz Univ Med Sci Sch Dent Tabriz Iran

Background/ Purpose. In terms of the detection of tooth diagnosis, no intelligent detection has been done up till now. Dentists just look at images and then they can detect the diagnosis position in tooth based on their experiences. Using new technologies, scientists will implement detection and repair of tooth diagnosis intelligently. In this paper, we have introduced one intelligent method for detection using particle swarm optimization (PSO) and our mathematical formulation. This method was applied to 2D special images. Using developing of our method, we can detect tooth diagnosis for all of 2D and 3D images. Materials and Methods. In recent years, it is possible to implement intelligent processing of images by high efficiency optimization algorithms in many applications especially for detection of dental caries and restoration without human intervention. In the present work, we explain PSO algorithm with our detection formula for detection of dental caries and restoration. Also image processing helped us to implement our method. And to do so, pictures taken by digital radiography systems of tooth are used. Results and Conclusion. We implement some mathematics formula for fitness of PSO. Our results show that this method can detect dental caries and restoration in digital radiography pictures with the good convergence. In fact, the error rate of this method was 8%, so that it can be implemented for detection of dental caries and restoration. Using some parameters, it is possible that the error rate can be even reduced below 0.5%.

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A new method for 3D city map generation

A new method for 3D city map generation

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IEEE Workshop on Signal processing systems (SIPS)

作者： xiaodan Zhang Guang Jiang Da Ai State Key Laboratory of Integrated Service Networks Xidian University Xi'an Shaanxi P. R. China The Key Laboratory of Electronic Information Application Technology of Site-survey of the Ministry of Public Security Xi'an University of Posts and Telecommunications Xi'an Shaanxi P. R. China

3D city map has been well studied in recent years. Ground laser scanner or airborne lidar are often used to collect 3D information in traditional 3D city map generation methods. As these systems are specially designed, they are usually expensive and complicate for mass marketing. This paper proposes a simple and fast 3D city map generation method, which relies on image-based reconstruction algorithms and the 2D satellite map. Firstly, we reconstruct the buildings and get the top-view outlines of buildings. Secondly, we use the coherent point drift (CPD) method to register the points on the top-view outlines with the points on the edges extracted from the 2D satellite map. Thus, the reconstructed 3D buildings can be exactly located in the satellite map. The experiment results demonstrate the validity of our method.

关键词： Three-dimensional displays Buildings image reconstruction Cities and towns Satellites image edge detection Solid modeling

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