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Application of Image processing technology in Building Surface Crack Detection

IOP Conference Series: Materials Science and Engineering 2019年第3期612卷

作者： Xin Xiong Li Huang Jinrong Tian Infrastructure and Logistics Management Wuhan University of Science and Technology Wuhan Hubei 430081 China College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan 430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan 430081 China Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Hubei Wuhan 430081 China

The phenomenon of cracks on the surface of buildings is widespread. The existence of cracks affects the normal use of buildings, shortening the service life, seriously damaging the structure of buildings, resulting in safety accidents. Therefore, regular detection and reinforcement of cracks on the surface of buildings is a necessary link to ensure safety. At present, the detection of building surface cracks is mainly carried out by manpower with means of equipment assisted. However, there are some problems in manpower detection, such as high manpower consumption, low *** paper presents a method of detecting and inspecting cracks on building surface based on image processing technology in machine vision, which includes image gray transformation, image denoising etc. Curve fitting and least square method are used to obtain crack parameters, so as to improve the inspecting efficiency and realize the automation of building surface inspection.

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Accurate spectral super-resolution from single RGB image using multi-scale CNN

arXiv

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arXiv 2018年

作者： Yan, Yiqi Zhang, Lei Li, Jun Zhang, Yanning Wei, Wei School of Electronics and Information Northwestern Polytechnical University Xi'an China School of Computer Science Northwestern Polytechnical University Xi'an China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology China Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation School of Geography and Planning Sun Yat-Sen University Guangzhou China

Different from traditional hyperspectral super-resolution ap-proaches that focus on improving the spatial resolution, spectral super-resolution aims at producing a high-resolution hyperspectral image from the RGB observation with super-resolution in spectral domain. However, it is challenging to accurately reconstruct a high-dimensional continuous spectrum from three discrete intensity values at each pixel, since too much information is lost during the procedure where the latent hyper-spectral image is downsampled (e.g., with ×10 scaling factor) in spectral domain to produce an RGB observation. To address this problem, we present a multi-scale deep convolutional neural network (CNN) to ex-plicitly map the input RGB image into a hyperspectral image. Through symmetrically downsampling and upsampling the intermediate feature maps in a cascading paradigm, the local and non-local image informa-tion can be jointly encoded for spectral representation, ultimately im-proving the spectral reconstruction accuracy. Extensive experiments on a large hyperspectral dataset demonstrate the effectiveness of the pro-posed method. Copyright © 2018, The Authors. All rights reserved.

关键词： Optical resolving power

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A Low-Area Overhead Secure Scan Architecture Resisting Scan-Based Attacks for Crypto Chips

A Low-Area Overhead Secure Scan Architecture Resisting Scan-...

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2017 International MultiConference of Engineers and computer Scientists, IMECS 2017

作者： Weizheng, Wang Jincheng, Wang Shuo, Cai Peng, Liu Tieqiao, Liu College of Computer and Communication Engineering Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and Technology Changsha Hunan410114 China College of Computer and Communication Engineering Changsha University of Science and Technology Changsha410114 China College of Computer and Communication Engineering Changsha University of Science and Technology Changsha410114 China Information Science and Engineering Department Hunan University Changsha410082 China Management School Hangzhou Dianzi University Hangzhou310018 China

ISBN: (纸本)9789881404732

Scan design is a widely used design-for-testability (DFT) technique that improves the controllability and observability of integrated circuits (ICs) resulting in the facilitation of the testing. However, it can also be used to access secret information of crypto chips, and thus threaten dramatically the security of the cipher keys. In this paper, we propose a secure scan DFT architecture to thwart scan-based side-channel attacks. This architecture provides the scan chain reset mechanism, and thus can prevent these attacks based on mode switching. Meanwhile, the secret key is isolated from scan chains of an advanced encryption standard (AES) design in the test mode. Therefore, it can also halt the test-mode-only scan attacks. The proposed secure scan DFT technique ensures the security without compromising the testability of original chip. Most important of all, the secure scan test is implemented with extremely low hardware overhead.

关键词： Design for testability

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An Energy Efficient VM Migration Algorithm in Data Centers

An Energy Efficient VM Migration Algorithm in Data Centers

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2017 16th International Symposium on Distributed Computing and Applications to Business,Engineering and Science（DCABES 2017）

作者： Xiaodong Wu Yuzhu Zeng Guoxin Lin Faculty of Mathematics and Computer Science Quanzhou Normal University Fujian Provincial Key Laboratory of Data Intensive Computing Key Laboratory of Intelligent Computing and Information ProcessingFujian Province University

In order to reduce operation and maintenance expense and also increase the resource utilization rate,server consolidation and virtualization solutions have been adopted in modern cloud computing data ***,the scheduling policies of virtual machine（VM） migration have been regarded as an effective method for energy *** this paper,we address the problem of VM consolidation in cloud data centers.A power aware scheduling algorithm THRUG,which is combined with a utilization threshold strategy and a VM selection policy,is *** tries to select the most appropriate VMs for migration each time when a physical machine（PM） is considered as being overloaded,such that the utilization of this PM is just not more than the utilization threshold,such that both the energy consumption and the number of VM migration can be *** experimental results show that compared with other algorithm,the proposed algorithm can effectively reduce the number of VM migrations as well as the energy consumption.

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Enhanced Geometric Map:a 2D&3D Hybrid City Model of Large Scale Urban Environment for Robot Navigation

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机器人 2016年第3期38卷 311-321页

作者： LI Haifeng HU Zunhe LIU Jingtai College of Computer Science and Technology Civil Aviation University of China Tianjin 300300 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou 350121 China Institute of Robotics and Information Automatic System Nankai University Tianjin 300071 China Tianjin Key Laboratory of Intelligent Robotics Tianjin 300071 China

To facilitate scene understanding and robot navigation in large scale urban environment, a two-layer enhanced geometric map(EGMap) is designed using videos from a monocular onboard camera. The 2D layer of EGMap consists of a 2D building boundary map from top-down view and a 2D road map, which can support localization and advanced map-matching when compared with standard polyline-based maps. The 3D layer includes features such as 3D road model,and building facades with coplanar 3D vertical and horizontal line segments, which can provide the 3D metric features to localize the vehicles and flying-robots in 3D space. Starting from the 2D building boundary and road map, EGMap is initially constructed using feature fusion with geometric constraints under a line feature-based simultaneous localization and mapping(SLAM) framework iteratively and progressively. Then, a local bundle adjustment algorithm is proposed to jointly refine the camera localizations and EGMap features. Furthermore, the issues of uncertainty, memory use, time efficiency and obstacle effect in EGMap construction are discussed and analyzed. Physical experiments show that EGMap can be successfully constructed in large scale urban environment and the construction method is demonstrated to be very accurate and robust.

关键词：被提高的几何学的地图都市模型机械手航运同时发生的定位而且映射局部的包裹调整

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Coarse-to-Fine Learning for Single-Image Super-Resolution

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IEEE Transactions on Neural Networks and Learning Systems 2017年第5期28卷 1109-1122页

作者： Zhang, Kaibing Tao, Dacheng Gao, Xinbo Li, Xuelong Li, Jie School of Computer and Information Science Hubei Engineering University Xiaogan Hubei432000 China Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway Street UltimoNSW2007 Australia State Key Laboratory of Integrated Services Networks School of Electronic Engineering Xidian University Xi'an Shaanxi710071 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 Video and Image Processing System Laboratory School of Electronic Engineering Xidian University Xi'an Shaanxi710071 China

This paper develops a coarse-to-fine framework for single-image super-resolution (SR) reconstruction. The coarse-to-fine approach achieves high-quality SR recovery based on the complementary properties of both example learning-and reconstruction-based algorithms: example learning-based SR approaches are useful for generating plausible details from external exemplars but poor at suppressing aliasing artifacts, while reconstruction-based SR methods are propitious for preserving sharp edges yet fail to generate fine details. In the coarse stage of the method, we use a set of simple yet effective mapping functions, learned via correlative neighbor regression of grouped low-resolution (LR) to high-resolution (HR) dictionary atoms, to synthesize an initial SR estimate with particularly low computational cost. In the fine stage, we devise an effective regularization term that seamlessly integrates the properties of local structural regularity, nonlocal self-similarity, and collaborative representation over relevant atoms in a learned HR dictionary, to further improve the visual quality of the initial SR estimation obtained in the coarse stage. The experimental results indicate that our method outperforms other state-of-the-art methods for producing high-quality images despite that both the initial SR estimation and the followed enhancement are cheap to implement. © 2012 IEEE.

关键词： Optical resolving power

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Comments on recent proposed Cui Et Al.’s KASE and Lu Et Al.’s dIBEKS schemes

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Journal of information Hiding and Multimedia Signal processing 2018年第1期9卷 162-169页

作者： Wu, Tsu-Yang Meng, Chao Wang, King-Hang Chen, Chien-Ming Pan, Jeng-Shyang Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No3 Xueyuan Road University Town Fuzhou350118 China National Demonstration Center for Experimental Electronic Information and Electrical Technology Education Fujian University of Technology No3 Xueyuan Road University Town Fuzhou350118 China School of Computer Science and Technology Harbin Institute of Technology Shenzhen Graduate School HIT Campus of University Town of Shenzhen Shenzhen518055 China Department of Computer Science and Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

Searchable encryption is a cryptographic primitive used to search an encrypted data in cloud storage. Recently, Cui et al. and Lu et al. proposed two variants of secure searchable encryption schemes, respectively. However, based on our best knowledge we demonstrate that the both schemes are insecure against different types of off-line keyword guessing attacks in this paper. Finally, we make discussions about searchable encryption schemes whether resisting off-line keyword guessing attacks. © 2018, Ubiquitous International. All rights reserved.

关键词： Cloud storage

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Learning convolutional neural network to maximize Pos@Top performance measure 25

Learning convolutional neural network to maximize Pos@Top pe...

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25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2017

作者： Geng, Yanyan Liang, Ru-Ze Li, Weizhi Wang, Jingbin Liang, Gaoyuan Xu, Chenhao Wang, Jing-Yan Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia Suning Commerce RandD Center USA Inc. Palo AltoCA94304 United States Information Technology Service Center Intermediate People's Court of Linyi City Linyi China Jiangsu University of Technology Jiangsu213001 China New York University Abu Dhabi Abu Dhabi United Arab Emirates

ISBN: (纸本)9782875870391

In the machine learning problems, the performance measure is used to evaluate the machine learning models. Recently, the number positive data points ranked at the top positions (Pos@Top) has been a popular performance measure in the machine learning community. In this paper, we propose to learn a convolutional neural network (CNN) model to maximize the Pos@Top performance measure. The CNN model is used to represent the multi-instance data point, and a classifier function is used to predict the label from the its CNN representation. We propose to minimize the loss function of Pos@Top over a training set to learn the filters of CNN and the classifier parameter. The classifier parameter vector is solved by the Lagrange multiplier method, and the filters are updated by the gradient descent method alternately in an iterative algorithm. Experiments over benchmark data sets show that the proposed method outperforms the state-of-the-art Pos@Top maximization methods. © ESANN 2017 - Proceedings, 25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. All rights reserved.

关键词： Convolution

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A Spatial Domain Quantum Watermarking Scheme

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Communications in Theoretical Physics 2016年第7期65卷 66-76页

作者：魏战红陈秀波徐淑奖钮心忻杨义先 School of Information Engineering Beijing Institute of Petrochemical Technology Information Security Center State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications State Key Laboratory of Information Security (Institute of Information Engineering Chinese Academy of Sciences) Shandong Provincial Key Laboratory of Computer Networks Shandong Computer Science Center(National Supercomputer Center in Jinan)

This paper presents a spatial domain quantum watermarking scheme. For a quantum watermarking scheme,a feasible quantum circuit is a key to achieve it. This paper gives a feasible quantum circuit for the presented scheme. In order to give the quantum circuit, a new quantum multi-control rotation gate, which can be achieved with quantum basic gates, is designed. With this quantum circuit, our scheme can arbitrarily control the embedding position of watermark images on carrier images with the aid of auxiliary qubits. Besides reversely acting the given quantum circuit, the paper gives another watermark extracting algorithm based on quantum measurements. Moreover, this paper also gives a new quantum image scrambling method and its quantum circuit. Differ from other quantum watermarking schemes, all given quantum circuits can be implemented with basic quantum gates. Moreover, the scheme is a spatial domain watermarking scheme, and is not based on any transform algorithm on quantum images. Meanwhile, it can make sure the watermark be secure even though the watermark has been found. With the given quantum circuit, this paper implements simulation experiments for the presented scheme. The experimental result shows that the scheme does well in the visual quality and the embedding capacity.

关键词： quantum cryptography quantum images quantum watermark spatial domain quantum watermark

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Multi-materials beam hardening artifacts correction for computed tomography (CT) based on X-ray spectrum estimation

arXiv

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arXiv 2018年

作者： Zhao, Wei Li, Dengwang Niu, Kai Qin, Wenjian Peng, Hao Niu, Tianye Key Laboratory of Computer Network and Information Integration Southeast University Ministry of Education Nanjing210096 China Shandong Province Key Laboratory of Medical Physics and Image Processing Technology School of Physics and Electronics Shandong Normal University Jinan250014 China Department of Medical Physics University of Wisconsin-Madison MadisonWI53705 United States Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Department of Physics Wuhan University Institute of Translational Medicine

Due to the energy dependent nature of the attenuation coefficient and the polychromaticity of X-ray source, beam hardening effect occurs when X-ray photons penetrate through an object, causing a nonlinear projection data. When a linear reconstruction algorithm, such as filtered backprojection, is applied to reconstruct the projection data, beam hardening artifacts which show as cupping and streaks, are present in the CT image. The aim of this study was to develop a fast and accurate beam hardening correction method which can deal with beam hardening artifacts induced by multi-materials objects. Based on spectrum estimation, the nonlinear attenuation process of the X-ray projection was modeled by reprojecting a template image with the estimated polychromatic spectrum. The template images were obtained by segmenting the uncorrected into different components using a simple segmentation algorithm. By adding the scaled difference of the monochromatic reprojection data and the polychromatic reprojection to the raw projection data, the raw projection data was mapped into the corresponding monochromatic projection data, which was used to reconstruct the beam hardening artifacts corrected images. The algorithm can also be implemented in image-domain which takes the uncorrected image volume as input. In this case, the scaled mapping term was reconstructed to yield a set of artifacts images which can be added directly to the uncorrected images. Numerical simulations, experimental phantom data and animal data which were acquired on a modern diagnostic CT scanner (Discovery CT750 HD, GE Healthcare, WI, USA) and a modern C-Arm CT scanner (Artis Zee, Siemens Healthcare, Forchheim, Germany), respectively, were used to evaluate the proposed method. The results show the proposed method significantly Copyright © 2018, The Authors. All rights reserved.

关键词： computerized tomography

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