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Research on edge detection algorithm Based on Line Laser Scanning

Procedia CIRP 2019年 84卷 1101-1106页

作者： Jingyi Tang Xiaoqun Tan Xi Li Binbin Wei Zhanxi Wang Chen Zheng School of Mechanical Engineering Northwestern Polytechnical University Xi’an 710072China SAIC Motor Technical Center Shanghai 210804China School of Aeronautics Northwestern Polytechnical University Xi’an 710072China

With the aim of obtaining the precise position of workpiece, it is necessary to detect the base hole during the automated manufacturing process of robotic drilling systems. In this paper, a detection method based on the line laser is presented to detect the base hole of large aviation parts in manufacturing and assembly. The 3-D point cloud data processing plays an important role during the detection process with a line laser. To extract the point cloud data effectively, an edge detection algorithm which includes a gradient-based edge extraction algorithm and an edge parameterization method is proposed. Then, the correlation analysis of the proposed algorithm is conducted. Finally, an industrial case is presented to illustrate the applicability and effectiveness of the proposed edge detection algorithm. The effects of varying the scan line spacing of the line laser are studied so as to meet the practical need of engineering application. The results indicate that the edge detection algorithm is applicable to the robotic drilling system, and it is reasonable and practicable to use the elliptic curve to parameterize the hole’s edge.

关键词： Base detection Line laser scanning edge detection algorithm Correlation analysis

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Image representation of structure color based on edge detection algorithm

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RESULTS IN PHYSICS 2020年 19卷

作者： Wen, Kui Zhang, Zhaojian Jiang, Xinpeng He, Jie Yang, Junbo Natl Univ Def Technol Ctr Mat Sci Changsha 410073 Peoples R China

The subwavelength structure based on metamaterials is widely used in the field of photonics due to its unique electromagnetic properties. Here, a Fabry-Perot-like cavity structure composed of aluminum and silicon materials is proposed, of which resonance peak can shift in the whole visible light band, and makes the materials display different colors. In addition, the edge detection algorithm is used to extract the edge position information of the image, so that the image represented by the structure color can be described more accurately. At the same time, the combination of structure color and algorithm upgrades the artificial representation of image information to intelligent processing. This work provides a valuable scheme for the design of simple nanostructures with multi physical mechanisms in the future.

关键词： Surface plasmon Structure color edge detection algorithm Image representation

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Application of temperature sensors and edge detection algorithms optimized based on thermal energy consumption in dance posture training

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THERMAL SCIENCE AND ENGINEERING PROGRESS 2025年 58卷

作者： Jin, Shanshan Chifeng Univ Educ Sci Coll Chifeng 024000 Inner Mongolia Peoples R China

In recent years, with the development of sensor technology and edge computing, new possibilities for dance posture training have been provided. The aim of this study is to develop a temperature sensor and edge detection algorithm based on thermal energy consumption optimization to improve the efficiency and accuracy of dance pose training. Wearable devices containing high-precision temperature sensors are able to monitor temperature changes in various parts of the dancer's body in real time. Through wireless transmission technology, this data is sent to edge computing devices for processing. edge computing devices use edge detection algorithms to quickly analyze a dancer's thermal consumption patterns and identify which postures or movements are causing excessive energy consumption. The results show that the temperature sensor and the edge detection algorithm can effectively monitor and analyze the dancers' thermal energy consumption. In the experiment, dancers trained with the system were able to get real-time feedback about changes in their body temperature, so that they could adjust their movements and training intensity in time. Compared with traditional training methods, dancers using this system have shown significant improvement in the optimization of energy consumption, training efficiency and effect have been improved, not only improve the scientific and accurate training, but also provide real-time feedback for dancers to help them manage their energy consumption more effectively.

关键词： Thermal energy consumption optimization Temperature sensor edge detection algorithm Dance posture Training application

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edge detection of infrared image with CNN_DGA algorithm

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OPTIK 2014年第1期125卷 464-467页

作者： Wang, Wei Yang, Li-Jun Xie, Yu-Ting An, You-wei Chongqing Univ Posts & Telecommun CQUPT Coll Elect Engn Chongqing 400065 Peoples R China

In this paper, infrared image edge detection algorithm based on the combination of the cellular neural networks (CNN) and distributed genetic algorithm (DGA) is proposed. The CNN template is used to train the network with distributed genetic algorithm (CNN_DGA). The experimental results show: the edge of the infrared image was extracted accurately with CNN_DGA edge detection algorithm;furthermore, the noise of the infrared image was reduced greatly. Compared with the edge detection algorithms based on cellular neural networks with template trained by particle swarm optimization, parameters' search range and convergence speed are greatly improved. (C) 2013 Elsevier GmbH. All rights reserved.

关键词： Infrared image process Cellular neural network distributed genetic algorithm (CNN_DGA) edge detection algorithm

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Automatic recognition of asphalt pavement cracks using metaheuristic optimized edge detection algorithms and convolution neural network

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AUTOMATION IN CONSTRUCTION 2018年 94卷 203-213页

作者： Nhat-Duc Hoang Quoc-Lam Nguyen Van-Duc Tran Duy Tan Univ Inst Res & Dev Fac Civil Engn P809-03 Quang Trung Danang 550000 Vietnam Duy Tan Univ Fac Civil Engn P809-03 Quang Trung Danang 550000 Vietnam Duy Tan Univ Int Sch 254 Nguyen Van Linh Danang 550000 Vietnam

Crack detection is a crucial task in periodic pavement survey. This study establishes and compares the performance of two intelligent approaches for automatic recognition of pavement cracks. The first model relies on edge detection approaches of the Sobel and Canny algorithms. Since the implementation of the two edge detectors require the setting of threshold values, Differential Flower Pollination, as a metaheuristic, is employed to fine-tune the model parameters. The second model is constructed by the implementation of the Convolution Neural Network (CNN) - a deep learning algorithm. CNN has the advantage of performing the feature extraction and the prediction of crack/non-crack condition in an integrated and fully automated manner. Experimental results show that the model based on CNN achieves a good prediction performance of Classification Accuracy Rate (CAR) = 92.08%. This performance is significantly better than the method based on the edge detection algorithms (CAR = 79.99%). Accordingly, the proposed CNN based crack detection model is a promising alternative to support transportation agencies in the task of periodic pavement inspection.

关键词： Pavement crack detection Convolution neural network Image processing edge detection algorithm Deep learning Metaheuristic

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Quality Assessment Methods to Evaluate the Performance of edge detection algorithms for Digital Image: A Systematic Literature Review

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IEEE ACCESS 2021年 9卷 87763-87776页

作者： Tariq, Nazish Hamzah, Rostam Affendi Ng, Theam Foo Wang, Shir Li Ibrahim, Haidi Univ Sains Malaysia Sch Elect & Elect Engn Engn Campus Nibong Tebal 14300 Malaysia Univ Tekn Malaysia Melaka Fak Teknol Kejuruteraan Elekt & Elekt Durian Tunggal 76100 Malaysia Univ Sains Malaysia Ctr Global Sustainabil Studies CGSS Hamzah Sendut Lib Level 5 Minden 11800 Malaysia Univ Pendidikan Sultan Idris Fac Art Comp & Creat Ind Tanjung Malim 35900 Malaysia

A segmentation process is usually required in order to analyze an image. One of the available segmentation approaches is by detecting the edges on the image. Up to now, there are many edge detection algorithms that researchers have proposed. Thus, the purpose of this systematic literature review is to investigate the available quality assessment methods that researchers have utilized to evaluate the performance of the edge detection algorithms. Due to the vast number of available literature in this area, we limit our search to only open-access publications. A systematic search in five publisher websites (i.e., IEEExplore, IET digital library, Wiley, MDPI, and Hindawi) and Scopus database was carried out to gather resources that are related to the edge detection algorithms. Seventy-three publications that are about developing or comparing edge detection algorithms have been chosen. From these publication samples, we have identified 17 quality assessment methods used by researchers. Among the popular quality assessment methods are visual inspection, processing time, confusion-matrix based measures, mean square error (MSE)-based measures, and figure of merit (FOM). This survey also indicates that although most of the researchers only use a small number of test images (i.e., less than 10 test images), there are available datasets with a larger number of images for digital image segmentation that researchers can utilize.

关键词： Image edge detection detection algorithms Quality assessment Systematics Bibliographies Image segmentation Digital images Digital image processing edge detection algorithm image segmentation assessment validation quality measures reviews

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Performance Analysis of edge detection algorithms with THEOS Satellite Images 2

Performance Analysis of Edge Detection Algorithms with THEOS...

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International Conference on Digital Arts, Media and Technology (ICDAMT) - Digital Economy for Sustainable Growth

作者： Boonarchatong, Chutiwan Ketcham, Mahasak Suan Dusit Univ Dept Informat Technol Bangkok Thailand King Mongkuts Univ Technol North Bangkok Dept Informat Technol Bangkok Thailand

ISBN: (纸本)9781509052103

The goal of this research is to find a suitable edge detection algorithm with 4 bands, B1, B2, B3, and B4 of different types of satellite image. In this paper, the dataset is derived from raw satellite images, namely THEOS, of the seashore in the Samut Prakan province, a fruit garden in the Chantaburi province and river line in Ayuthaya provinces. edge detection performance algorithms are Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), and edge detection processing time, as well as qualitative human visual perception. Our result shows that Canny algorithm and Laplacian of Gaussian algorithm were the best edge detection algorithm for both qualitatively and quantitatively. Moreover, the different kinds of bands in satellite images illustrated the same result. All of the algorithms consumed similar times.

关键词： Satellite Images Performance Analysis edge detection algorithm

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Intensity gradient based edge detection for pixelated communication systems

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JOURNAL OF ENGINEERING-JOE 2019年第12期2019卷 8463-8470页

作者： Kabir, Md Ahasan Mondal, Md Rubaiyat Hossain Chittagong Univ Engn & Technol Dept Elect & Telecommun Engn Chittagong Bangladesh Bangladesh Univ Engn & Technol Inst Informat & Commun Technol Dhaka Bangladesh

Pixelated optical communication systems transmit data using a series of encoded pixelated images. The decoding of these pixelated images is important for reliable data communication. This study proposes a novel intensity gradient-based edge detection (IGED) method for the received pixelated images. In the first stage of the proposed edge detection algorithm, the intensity difference of neighbouring pixels is calculated in the horizontal or vertical direction depending on the presence of a horizontal or vertical edge. In the second stage, the false edge pixels whose intensity values are less than the threshold are removed. Next, slopes are calculated between the consecutive edge pixels and the appropriate lines are found considering the slopes that have almost the same value. The new IGED method performs edge detection without requiring any anchor pixel blocks. This study also provides a description of a misalignment correction algorithm suitable for pixelated images. Next, the effectiveness of the proposed IGED method is tested through an experimental demonstration. It is shown that the IGED method can properly detect the edges even for pixelated images affected by rotational misalignment. For a given transmitter resolution, the proposed method provides better data rates than the existing methods.

关键词： gradient methods edge detection data communication reliable data communication novel intensity gradient-based edge detection method received pixelated images edge detection algorithm intensity difference neighbouring pixels horizontal edge vertical edge false edge pixels whose intensity values consecutive edge pixels IGED method anchor pixel blocks intensity gradient based edge detection pixelated communication systems pixelated optical communication systems encoded pixelated images

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Optimizing tool orientations for 5-axis machining by configuration-space search method

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COMPUTER-AIDED DESIGN 2003年第6期35卷 549-566页

作者： Jun, CS Cha, K Lee, YS Gyeongsang Natl Univ Div Ind & Syst Engn Gyeongnam 660701 South Korea Georgia Inst Technol Sch Ind & Syst Engn Atlanta GA 30332 USA N Carolina State Univ Dept Ind Engn Raleigh NC 27695 USA

This paper presents a methodology and algorithms of optimizing and smoothing the tool orientation control for 5-axis sculptured surface machining. A searching method in the machining configuration space (C-space) is proposed to find the optimal tool orientation by considering the local gouging, rear gouging and global tool collision in machining. Based on the machined surface error analysis, a boundary search method is developed first to find a set of feasible tool orientations in the C-space to eliminate gouging and collision. By using the minimum cusp height as the objective function, we first determine the locally optimal tool orientation in the C-space to minimize the machined surface error. Considering the adjacent part geometry and the alternative feasible tool orientations in the C-space, tool orientations are then globally optimized and smoothed to minimize the dramatic change of tool orientation during machining. The developed method can be used to automate the planning and programming of tool path generation for high performance 5-axis sculptured surface machining. Computer implementation and examples are also provided in the paper. (C) 2002 Elsevier Science Ltd. All rights reserved.

关键词： 5-axis CNC machine sculptured surface machining optimal tool orientation configuration space search edge detection algorithm CAD/CAM

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Optimisation of calculation methods for determination of surface tensions by drop profile analysis tensiometry

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ADVANCES IN COLLOID AND INTERFACE SCIENCE 2007年 134-35卷 322-329页

作者： Zholob, S. A. Makievski, A. V. Miller, R. Fainennan, V. B. Donetsk Med Univ Physicochem Ctr UA-83003 Donetsk Ukraine SINTERFACE Technol D-12489 Berlin Germany MPI Colloids & Interfaces D-14424 Potsdam Germany

The standard technique for measuring surface or interfacial tension by drop profile analysis requires two main steps: (i) acquisition of drop/bubble images and determination of the profile coordinates via edge detection techniques;(ii) fitting of the theoretical drop/bubble profile to the experimental coordinates using the interfacial tension T as adjustable parameter. As to edge detection technique, usually the position of the maximum grey level gradient is assumed to be the drop edge. In order to increase the accuracy of edge detection the procedure of fitting a normal distribution function to the experimental grey level gradients yields accurate results when the drop edge is located into the distribution centre. Conventional algorithms use the arc length along the drop profile as independent variable and fit in a vertical, horizontal or normal direction to the experimental shape coordinates, requiring that the coordinates have to be interpolated between experimental points. For small drops having an almost spherical shape, this technique leads to rather large errors. To avoid this interpolation problem a transformation of the Gauss-Laplace equation into polar coordinates can provide higher accuracy. For this, the angle of rotation is used as independent variable and the origin of the coordinate system is located exactly between the drop apex and the capillary tip at which the drop or bubble is formed. (c) 2007 Published by Elsevier B.V.

关键词： Gauss-Laplace equation of capillarity edge detection algorithm drop profile analysis tensiometry polar coordinate system

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