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检索条件"主题词=Image Edge Detection"

共 27763 条记录，以下是131-140 订阅

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New image edge detection Approach by Using Grey Entropy

New Image Edge Detection Approach by Using Grey Entropy

引用

International Symposium on Knowledge Acquisition and Modeling, KAM

作者： Gang Li Yala Tong Xinping Xiao School of Science Wuhan University of Technology Wuhan Hubei China School of Science Hubei University of Technology Wuhan Hubei China

The paper put forward a new method of image edge detection based on grey entropy which was the first time to be applied into the field of image edge extraction. We let the median value of pixels in the neighborhood of the window be the reference sequence, and selected certain pixels from sixteen different directions as the comparative sequences according to the information of the image texture and pixel distribution. After carrying out the grey relational analysis, we employed the grey relational coefficients obtained to calculate the grey entropy. If the difference between the maximum grey entropy value and the minimum one is greater than a given threshold, we can determine the central pixel is an edge point, or it is a non-edge one. Experiments show that this method can achieve a better effect than other conventional algorithms, and it provides us a new approach to image edge detection.

关键词： image edge detection Entropy Pixel image processing image analysis image sequence analysis Knowledge acquisition Industrial relations Solid modeling Size measurement

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The Multispectral image edge detection Based on Clifford Gradient

The Multispectral Image Edge Detection Based on Clifford Gra...

引用

International Conference on Computational Intelligence and Security

作者： Hui Liu Chen Xu Wenming Cao College of Information Engineering Shenzhen University Shenzhen China Guangdong University of Foreign Studies (GDUFS) Guangzhou China College of Mathematics and Computational Science Shenzhen University Shenzhen China

ISBN: (纸本)9781457720086

Taking full advantage of the multispectral properties of multispectral image, we should get the exceptional accurate edge. Clifford algebra is suit for dealing the multidimensional data, and can give expression to the association of the data better than the general algebra. It is a very rewarding method that to via Clifford algebra to get the edge of the multispectral image. In the paper, we discuss the base properties of Clifford algebra firstly, and then detail the Clifford algebra description of the multispectral image. Lastly the new Multispectral image edge detection algorithm is proposed, which is based on the Clifford gradient. Compared the algorithm with maximal entropy edge detection algorithm in experiments, we generalize a conclusion that the new method can retain the more perfect edge information of the image.

关键词： image edge detection Vectors Algorithm design and analysis Entropy Signal processing algorithms image color analysis

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An improved image edge detection algorithm based on fuzzy sets

An improved image edge detection algorithm based on fuzzy se...

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International Conference on Multimedia Technology

作者： Yanhong Wang Denghui Li Yaning Xu Guangxi key laboratory of information and communication Guilin University of Electronic and Technology Guilin China Institute of Information Technology Guilin University of Electronic and Technology Guilin China College of Intentional Exchange Guilin University of Electronic and Technology Guilin China

ISBN: (纸本)9781612847719

An improved image edge detection algorithm based on generalized fuzzy sets is proposed in order to overcome the shortcomings of the traditional algorithm. A new membership function is reconstructed in this paper, and it maps the image from space domain to fuzzy domain. The image is processed by enhance operator. Finally, the fuzzy membership value is transformed with inverse operation, and the image's edge gray value is got. The results show that the improved algorithm effectively reduces the computation and improves the image quality. Therefore the improved algorithm in this paper is more effective.

关键词： image edge detection Manganese Algorithm design and analysis Fuzzy sets Noise Biomedical imaging

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A Matrix Coding Genetic Algorithm Based on Memristor for image edge detection 23

A Matrix Coding Genetic Algorithm Based on Memristor for Ima...

引用

Proceedings of the 2023 9th International Conference on Communication and Information Processing

作者： Zhong Xuefeng Yu Yongbin Zhou Chen Wang Xiangxiang Feng Xiao Zhou Zhexian Shen Jiarun Wang Jingya Han Xinyi University of Electronic Science and Technology of China China

ISBN: (纸本)9798400708909

Researchers have shown the feasibility of memristive networks for some swarm intelligence algorithms like Ant Colony Algorithm (ACO). In this paper, a matrix-based Genetic Algorithm (MGA) for image edge detection is proposed, which means the evolution process of Genetic Algorithm (GA) is transformed to matrix computation in the application of image edge detection. Secondly, memristor circuits are designed and mapping relationship between memristor and GA is built up for the deployment of GA operators. Thirdly, the simulation results of memristor circuits show the feasibility of deploying GA with memristors and the experiment results compared with other memristor-based swarm intelligence algorithms illustrate the effectiveness and superiority of the proposed method. (MCGABM) Finally, two methods are adopted as novel evaluation indicators for the image edge detection to discuss the performance of the proposed algorithm more objective.

关键词： genetic algorithm image edge detection memristor

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An algorithm for image edge detection using improved PCNN

An algorithm for image edge detection using improved PCNN

引用

IEEE International Conference on Granular Computing (GRC)

作者： Lan Di Yi Lin Li Liu School of Information Technology Jiangnan University Wuxi China School of Computer Science & Technology Southwest National University Chengdu China

A calculated method is proposed which uses the region areas to modulate the pulse of the corresponding neurons in PCNN. The edge detection for the blurred image with noise can reduce the noise and obtain a precise edge value of the image. First, based on the analysis of the difference between the edge pixels and the noise pixels, it proposes a method, which suppresses the noise by the region areas. Second, it suggests that image segmentation uses the pulse of the corresponding neurons in PCNN. The experimental results show that this method is effective and feasible.

关键词： image edge detection Joining processes Pulse modulation Noise reduction image segmentation Neurons Neural networks Object recognition Shape measurement Pulse generation

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The Application Multi-scale Characteristics of the Rubber Gasket image edge detection by Using Wavelet

The Application Multi-scale Characteristics of the Rubber Ga...

引用

ETT and GRS International Education Technology and Training, and International Workshop on Geoscience and Remote Sensing

作者： Changhua Lu Yi Zhang Mei Han Chun Liu College of Computer and Information Management Hefei university of technology Hefei Anhui China

This paper is based on the multi-scale analysis of the wavelet transform. By detecting the part modulus maximum of the planar wavelet transformation coefficient, it can acquire the image edge feature of the rubber gasket and demonstrate the feasibility and advantages of Gaussian function, especially the smoothing function. This method successfully retains the edge information of rubber gasket and clearly detects its defects. The experiment proves that this novel method is able to extract the image edge from industrial image which contains uncertain and unclear edges.

关键词： Rubber Gaskets image edge detection Wavelet analysis image resolution Wavelet transforms Large-scale systems Arithmetic Educational technology image analysis

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A short step affine transformation Sobel algorithm based image edge detection in low illumination

A short step affine transformation Sobel algorithm based ima...

引用

Chinese Automation Congress (CAC)

作者： Yiwen Dou Kuangrong Hao Yongsheng Ding Engineering Research Center of Digitized Textile & Apparel Technology Donghua University Shanghai P. R. China

An object within low illumination image is difficult to distinguish and its contour needs fast computing speed in real-time visual detection systems. Aiming at above problem, a short step affine transformation (SSAT) Sobel algorithm for image edge detection is represented. First, static image needs to do affine transformation. The corresponding gradient image will be obtained after transformed image with partial derivative calculation. Then using parameter model with short step constraint, it will get the gradient different image. The last operation is to select an appropriate threshold to segment the gradient different image. Compared with one order and two order edge algorithms, SSAT Sobel algorithm can guarantee to get the right edge of image as well as meeting the real time requirements of the visual system.

关键词： image edge detection Lighting Algorithm design and analysis Real-time systems Nonhomogeneous media image databases image segmentation

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A Fully Automatic Approach of Color image edge detection

A Fully Automatic Approach of Color Image Edge Detection

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Yangxing Liu Takeshi Ikenag Satoshi Goto Graduate School of Information Production and Systems Waseda University Kitakyushu Japan

edge detection is a vital pre-processing step of many image analysis systems. In this paper, we intend to present a novel algorithm to automatically extract color image edge by integrating multi-dimensional gradient analysis and statistical analysis on local regions. Compared with previous gradient-based edge detection algorithms, our algorithm does not need to select an appropriate threshold against the gradient magnitude. With an elaborate edge detector, we exploit image pixel gradient direction, magnitude, spatial information and region property to obtain color image edge. To avoid the problem of detecting false edges, we conduct statistical analysis on certain local regions, which have high edge density, to further optimize our edge detection result. Experimental results demonstrate the performance of our algorithm on different color images.

关键词： image edge detection Detectors Statistical analysis Pixel image color analysis image processing Production systems Eigenvalues and eigenfunctions Cybernetics Data mining

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A New image edge detection Algorithm Based on Measuring of Medium Truth Scale

A New Image Edge Detection Algorithm Based on Measuring of M...

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IEEE International Conference on Networking, Sensing and Control

作者： Ning-ning Zhou Zheng-xu Zhao Long Hong Yu-long Deng School of Instrument Science and Engineering South-East University Nanjing China Nanjing University of Posts and Telecommunications Nanjing China School of Instrumentation Science and Engineering South-East University Nanjing China School of computing University of Derby UK School of Computer Nanjing University of Posts and Telecommunications Nanjing China

image edge is a basic feature of images, and edge detection is a preprocessing technique in the field of image processing. This paper presents a novel image edge detection algorithm derived from the similarity degree of edge pixels based on the measuring of medium truth scale. For further edge refining, two thresholds and restraint on non-minimum value in domain are applied to the algorithm. Simulation results show that the algorithm can effectively eliminate noise , successfully preserve the image edge details, produce better edge detection result and is more effective and have wider applications compared with that of the classic algorithms.

关键词： image edge detection Mathematics Telecommunication computing Detectors Fuzzy set theory Educational institutions image recognition Instruments image processing Pixel

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A hybrid approach for color based image edge detection

A hybrid approach for color based image edge detection

引用

International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Chinu Amit Chhabra Department of Computer Science and Engineering Guru Nanak Dev University Amritsar Punjab

edge detection is an elementary step used in various image processing applications. The main problems in existing edge detection algorithms are poor edge localization, less noise removal capacity, unable to detect edges in complex background images and inability to properly detect the color edges in images. In this paper a sequential hybrid approach is proposed to overcome all the limitations of existing edge detection algorithms. The operations performed by image edge detection algorithm can be computationally expensive and takes lots of execution time for processing the data. This research work also improves hybrid color based image edge detection technique by using the data parallelism approach. The comparison among sequential and parallel edge detection will be drawn based upon different parallel metrics. The experimental results have shown that parallel strategy achieves a performance gain of 68% as compared to sequential approach.

关键词： image edge detection image color analysis Vectors PSNR Colored noise

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