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16th International Conference on Ground Penetrating Radar (GPR)

作者： Che, J. K. Chen, C. C. Stolarczyk, L. G. Ohio State Univ 1330 Kinnear Rd Columbus OH 43212 USA Stolar Horizon Inc Raton NM 87740 USA

ISBN: (纸本)9781509051816

A novel sensor was previously developed for detecting rock boundaries behind uncut coal for controlling the horizon of the cutting head in long-wall mining environments. This boundary detection method is based on extracting the thickness of the uncut layer from the complex reflection coefficient of a narrow band antenna that is mounted directly on the rotating cutting drum. The main practical challenges of this detection method lie in the ability to (1) mitigate the much stronger reflection from the air-mine interface and (2) obtain the in situ dielectric constant and conductivity of the cut material in active mining environments. This paper presents a novel in situ calibration method and real-time uncut thickness estimation procedure which could be practically implemented into normal long-wall mining operations, and thus allowing real-time monitoring of distance to rock boundaries behind the uncut seam. This paper will also discuss the uncertainty of the resultant estimated thickness in relation to the variation of cutting drum positions, dielectric constant, and air gap.

关键词： Self-Calibrated boundary detection algorithm Single Frequency

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An Online Local boundary detection and Classification algorithm for Networked Multi-Robot Systems

An Online Local Boundary Detection and Classification Algori...

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International Conference on Advanced Technologies for Communications (ATC)

作者： Pham Duy Hung Tran Quang Vinh Trung-Dung Ngo Univ Engn & Technol Hanoi Vietnam Univ Brunei Darussalam More Than One Robot Lab Bandar Seri Begawan Brunei Univ Prince Edward Isl Charlottetown PE Canada

ISBN: (纸本)9781509027118

We present an online boundary classification error detection algorithm to improve accuracy of the original distributed boundary detection algorithm for networked multi-robot systems. It is a fully decentralized method based on the geometric approach allowing to suppress boundary errors without recursive process and global synchronization. The accuracy of the ration of correctly identified robots over the total number of robots reaches 100%. We have demonstrated the effectiveness of this boundary detection algorithm in both simulation and real-world environment.

关键词： Robot sensing systems detection algorithms Nickel Robot kinematics Image edge detection Multi-robot systems multi-robot systems Edge detection Manipulator sensing systems Robot kinematics detection algorithms boundary detection algorithm Sorting algorithm Nickel Robot

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Radar HRRP Open Set Target Recognition Based on Closed Classification boundary

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REMOTE SENSING 2023年第2期15卷 468-468页

作者： Xia, Ziheng Wang, Penghui Liu, Hongwei Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China

Radar automatic target recognition based on high-resolution range profile (HRRP) has become a research hotspot in recent years. The current works mainly focus on closed set recognition, where all the test samples are assigned to the training classes. However, radar may capture many unknown targets in practical applications, and most current methods are incapable of identifying the unknown targets as the 'unknown'. Therefore, open set recognition is proposed to solve this kind of recognition task. This paper analyzes the basic classification principle of both recognitions and makes sure that determining the closed classification boundary is the key to addressing open set recognition. To achieve this goal, this paper proposes a novel boundary detection algorithm based on the distribution balance property of k-nearest neighbor objects, which can be used to realize the identification of the known and unknown targets simultaneously by detecting the boundary of the known classes. Finally, extensive experiments based on measured HRRP data have demonstrated that the proposed algorithm is indeed helpful to greatly improve the open set performance by determining the closed classification boundary of the known classes.

关键词： open set recognition HRRP closed classification boundary boundary detection algorithm k-nearest neighbor

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An Improved Connectivity-based boundary detection algorithm in Wireless Sensor Networks

An Improved Connectivity-based Boundary Detection Algorithm ...

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38th Annual IEEE Conference on Local Computer Networks (LCN)

作者： Huang, Baoqi Wu, Wei Zhang, Tao Inner Mongolia Univ Coll Comp Sci Hohhot 010021 Peoples R China Neimenggu Mobile Commun Co Ltd Hohhot Peoples R China

ISBN: (纸本)9781479905379

This paper tackles the problem of boundary detection by proposing a simple, distributed and connectivity-based algorithm. Our algorithm examines the 2-hop iso-contour of each node, and outperforms existing algorithms examining iso-contours. Specifically, the proposed algorithm makes a rough decision on a suspected boundary node by examining its 2-hop iso-contour, and then refines the decision based on a heuristic operation, which significantly reduces the size of the suspected boundary node set. More importantly, boundary cycles corresponding to inner and outer boundaries are identified and provide valuable knowledge to various applications. A thorough evaluation shows that our algorithm is applicable to dense as well as sparse WSNs.

关键词： boundary detection algorithm Wireless sensor networks Edge detection algorithms boundary layer Line of nodes boundary Dense Tackles

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Tool thermal deformation measurement research based on image processing technology

Tool thermal deformation measurement research based on image...

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Electron Device and Mechanical Engineering (ICEDME), International Conference on

作者： Kuo Wang Changlong Zhao Qiyin Lv Xuxu Wang Shihang Yao Jun Liu Mechanical and Vehicle Engineering Changchun University Changchun Jilin China

ISBN: (数字)9781728181455

ISBN: (纸本)9781728181462

Aiming at the problem of tool deformation during machine preheating, a tool thermal deformation measurement scheme based on image processing was designed to analyze the relationship between the position change of tool axial due to thermal error and the preheating time. High speed camera was used to collect tool images, and canny algorithm was used to extract rough positioning of the edges of the images combined with matlab software. Subpixel fitting edge detection method was used to precisely locate the tool edge contour, that is, the least square method was used to fit the tool tip curve and calculate the size of tool deformation. The accuracy of tool deformation measurement can reach micron level.

关键词： image processing edge detection least square method tool thermal deformation Least squares method Image processing Edge detection changes position boundary detection algorithm digital image processing techniques deformation

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A FPGA Verification of Improvement Edge detection using Separation and Buffer Line

A FPGA Verification of Improvement Edge Detection using Sepa...

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International Conference on Electronics, Information and Communications (ICEIC)

作者： Tao Peng Thathupara Subramanyan Kavya Erdenetuya Young-Min Jang Sang-Bock Cho School of Electrical Engineering University of Ulsan Ulsan Republic of Korea

ISBN: (数字)9781728162898

ISBN: (纸本)9781728162904

This paper investigates the performance of an improved edge detection algorithm on an FPGA platform. The algorithm has three blocks: gray scale and Gaussian filter, separation and buffer line, Prewitt filter. Separation and buffer line method are needed to improve edge detection speed. Therefore, when converting to frames per second, the speed is improved to 183frames/s, which is faster than conventional method. A proposed algorithm was implemented using Matlab program and it is verified through a RTL-level simulation of ISE14.3.

关键词： edge detection field programmable gate arrays hardware description languages image filtering Field programmable gate arrays Edge detection Hardware design languages image filtering boundary detection algorithm Grey scale Separation separation

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Efficient OpenCL Accelerators for Canny Edge detection algorithm on a CPU-FPGA Platform

Efficient OpenCL Accelerators for Canny Edge Detection Algor...

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International Conference on Reconfigurable Computing and FPGAs (ReConFig)

作者： Samah Rahamneh Lina Sawalha Computer and Electrical Engineering Western Michigan University Kalamazoo MI

ISBN: (纸本)9781728119588

The processing demands of current and emerging applications, such as image/video processing, are increasing due to the deluge of data, generated by mobile and edge devices. This raises challenges for a vast range of computing systems, starting from smart-phones and reaching cloud and data centers. Heterogeneous computing demonstrates its ability as an efficient computing model due to its capability to adapt to various workload requirements. Field programmable gate arrays (FPGAs) provide power and performance benefits and have been used in many application domains from embedded systems to the cloud. In this paper, we used a closely coupled CPU-FPGA heterogeneous system to accelerate a sliding window based image processing algorithm, Canny edge detector. We accelerated Canny using two different implementations: Code partitioned and data partitioned. In the data partitioned implementation, we proposed a weighted round robin based algorithm that partitions input images and distributes the load between the CPU and the FPGA based on latency. The paper also compares the performance of the proposed accelerators with separate CPU and FPGA implementations. Using our hybrid CPU-FPGA based algorithm, we achieved a speedup up to 4.8× over a CPU-only and up to 2.1× over a FPGA-only implementations. Moreover, the estimated total energy consumption of our algorithm is more efficient than a CPU-only implementation. Our results show a significant reduction in energy delay product (EDP) compared to the CPU-only implementation, and comparable EDP results to the FPGA-only implementation.

关键词： edge detection embedded systems field programmable gate arrays Field programmable gate arrays Embedded systems Edge detection partitions Accelerators algorithms boundary detection algorithm central processing units Deluge sliding windows Electronic Data Processing Clouds data center

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Performance Analysis of Edge detection algorithms for Object detection in Accident Images

Performance Analysis of Edge Detection Algorithms for Object...

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Global Conference for Advancement in Technology (GCAT)

作者： P. Joyce Beryl Princess Salaja Silas Elijah Blessing Rajsingh Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (纸本)9781728136950

Identifying the severity of the collision in road accidents helps in suitable extricate operation to be initiated immediately. Detecting the objects in accident images demands analyzing the vehicle type, number of vehicles and the severity of collision. Edge detection is used in identifying various objects such as vehicles and victims by outlining the sudden change of pixel intensity from the given accidental images. Prewitt, Roberts, Canny, Sobel, and Laplacian of Gaussian are the predominant edge detection algorithms in literature. Identifying and applying the suitable edge detection algorithm is critical for efficient object detection in accident images. In this paper, the performance of the aforementioned algorithm was evaluated in terms of Peak Signal-to-Noise Ratio (PSNR) and Mean Square Error (MSE). The experimental results show that the Sobel edge detection algorithm is suitable for edge detection in accident images.

关键词： edge detection mean square error methods object detection road accidents traffic engineering computing Object detection boundary detection algorithm Mean square error Road accidents Edge detection engineering computing Accidents vehicle images

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Fast Laplacian of Gaussian Edge detection algorithm for Quantum Images

Fast Laplacian of Gaussian Edge Detection Algorithm for Quan...

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IEEE International Symposium on Parallel and Distributed Processing with Applications and IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Suzhen Yuan Salvador E. Venegas-Andraca Chaoping Zhu Yan Wang Xuefeng Mao Yuan Luo College of opto electronic engineering Chongqing University of Posts and Telecommunications Chongqing China Escuela de Ingenieria y Ciencias Tecnologico de Monterrey Mexico Mexico School of Artificial Intelligence Chongqing Technology and Business University Chongqing China

ISBN: (纸本)9781728152103

Quantum image processing, which is the application of quantum theory in image processing, has attracted increasing attention in recent years. In this paper, we propose a framework of Laplacian of Gaussian (LoG) edge detection algorithm for quantum images. The LoG is commonly employed as a second-order edge detector in image processing. Firstly, discrete LoG mask is obtained from the continuous Gaussian operator within certain detection error. Secondly, filter the quantum image with the LoG mask. Thirdly, to obtain the edge image, the searching for zero-crossing point of the filtered image is proposed. Finally, the time complexity is analyzed, which shows that this quantum LoG operator has polynomial-time complexity.

关键词： computational complexity edge detection Gaussian processes image filtering Laplace equations quantum computing complexity classes Laplace's equation image filtering Edge detection Gaussian processes quantum computing boundary detection algorithm Laplacian operator Image processing edge image quanta logs logarithm (log) Error detection Gauss

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Quantitative Analysis of Nanopore Structural Characteristics of Lower Paleozoic Shale, Chongqing (Southwestern China): Combining FIB-SEM and NMR Cryoporometry

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ENERGY & FUELS 2017年第12期31卷 13317-13328页

作者： Tong, Shaoqing Dong, Yanhui Zhang, Qian Elsworth, Derek Liu, Shimin Chinese Acad Sci Inst Geol & Geophys Key Lab Shale Gas & Geoengn Beijing 100029 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Inst Earth Sci Beijing 100029 Peoples R China Penn State Univ Dept Energy & Mineral Engn Ctr G3 University Pk PA 16802 USA Penn State Univ EMS Energy Inst University Pk PA 16802 USA

Characterizing nanopore structure is one of the most important factors in understanding gas storage and transport in shale reservoirs, but remains a significant challenge. In this work, we combine the benefits of Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) and Nuclear Magnetic Resonance Cryoporometry (NMR-C) to characterize the nanopore structure of lower Paleozoic shales from Chongqing, southwestern China. Mineral composition is qualified through X-ray Energy Dispersive Spectroscopy (EDS) and Field-Emission Scanning Electron Microscopy (FE-SEM). Voids in 2D micrographs are classified into types of meso- and/or microfractures, inter particle pores (InterP pores), intraparticle pores (IntraP pores), and pores in organic matter (OM pores). An Otsu thresholding algorithm and an edge detection algorithm (in Avizo) are used to segment OM, InterP, and IntraP pores and to establish 3D pore structure for pore-network modeling (PNM). The pore size distribution (PSD) is measured via PNM and compared to the PSD recovered from NMR-C. Results indicate that the small OM pores have favorable potential for storing adsorbed gas because of their apparent interconnectivity and higher porosity;conversely, InterP and IntraP pores are mostly isolated and with low porosity. The peaks of the PSD, recovered from PNM, are in the ranges 10-20 nm and 60-120 nm and are in good agreement with the peaks of the PSD recovered from NMR-C. This suggests that the NMR signals in these discontinuous ranges are due to OM, InterP, and IntraP pores. This indirectly demonstrates that the probe liquid in the NMR-C experiments (i.e., water) may indeed enter the nanoscale pores in the shale during centrifugal saturation. Comparison of the PSD from PNM and NMR-C also shows that NMR-C has a higher sensitivity and accuracy in detecting nanopores. Combining FIB-SEM and NMR-C is a promising technique in detecting and characterizing the nanoporosity of shales.

关键词： Pulse Number Modulation lower Paleozoic Southwestern China boundary detection algorithm Nanopores Focused Ion Beam-Scanning Electron Microscope shale QUANTITATIVE ANALYSIS Cryoporometry

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