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检索条件"主题词=Image Edge detection"

共 27915 条记录，以下是131-140 订阅

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X-Ray image edge detection Based on Wavelet Transform and Lipschitz Exponent

X-Ray Image Edge Detection Based on Wavelet Transform and Li...

引用

International Symposium on Intelligent Information Technology and Security Informatics, IITSI

作者： Guowei Tang Xiaoqing Zhong Fangzhou Zhang Zhenying Jin College of Computer and Information Technology Daqing Petroleum Institute Daqing China Daqing Drilling Group The Second Geological Logging Company Songyuan China

The characteristics of X-ray testing image are analyzed and an edge detection algorithm based on the multi-scale and multi-resolution of wavelet transform is proposed. According to the propagation of modulus maximum under different scales and the relationship between wavelet transform and Lipschitz exponent, the local maxima in vertical, horizontal and diagonal directions are detected by quadratic B-spline and Mallat algorithm was used in wavelet decomposition to determine defect edges. The experiment results prove that the algorithm of edge detection works fine the X-ray images.

关键词： X-ray imaging image edge detection Wavelet transforms X-ray detection X-ray detectors Welding image analysis Pipelines Information technology Wavelet analysis

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Boundary points handling for image edge detection based on Neutrosophic set

Boundary points handling for image edge detection based on N...

引用

International Conference on Knowledge-Based Engineering and Innovation (KBEI)

作者： Elyas Rashno Behrouz Minaei-Bidgoli Department of computer engineering Iran University of science and technology Tehran Iran

In this work, a new approach based on Neutrosophic set (NS) is proposed for image edge detection. At first, a new definition for boundary points in NS domain is presented. Then, a new cost function is designed to separate boundary points from other points. Finally, each data point is assigned to main, boundary and outlier clusters with 3 membership degrees. After these assignments, points with higher membership degrees to boundary cluster are considered as edge pixels. The proposed method is evaluated in two types of image datasets including artificial and real images. Results demonstrated that the proposed method detects edges more efficiently and accurately in comparison to state of the art edge detection algorithms.

关键词： image edge detection image segmentation Noise measurement Cost function Signal to noise ratio Uncertainty

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COLOUR image edge detection USING QUATERNION QUANTIZED LOCALIZED PHASE

COLOUR IMAGE EDGE DETECTION USING QUATERNION QUANTIZED LOCAL...

引用

European Signal Processing Conference

作者： Soo-Chang Pei Yu-Zhe Hsiao Grad. Inst. of Commun. Eng. Nat. Taiwan Univ. Taipei Taiwan

Recently, a novel edge detection method for gray-level image using quantized localized phase was proposed in [1]. The rationale of this method for edge detection is that we can obtain more edge and contour information of interested image from its quantized localized phase rather than from its magnitude. This is because the phase information is of greater importance on edge areas than on smooth areas. In this paper, we generalize the method in [1] to deal with colour image edge detection using quaternion polar form and two dimensional quaternion short-term Fourier transform (2-D QSTFT). By applying 2-D QSTFT to colour image, locally quantizing the phase part of quaternion polar form of the transformed image, and then reconstructing the resulted image using 2-D QISTFT and quantized phase, we can preserve the edge information and therefore achieve the goal of colour image edge detection.

关键词： Quaternions image edge detection image color analysis Fourier transforms image reconstruction

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An Algorithm for Remote Sensing image edge detection Based on Fuzzy Sets

An Algorithm for Remote Sensing Image Edge Detection Based o...

引用

International Symposium on Intelligent Information Technology Application, IITA

作者： Gang Li Fan Yang Linlin Wang Coll. of Autom. Chongqing Univ. Chongqing Coll. of Comput. Sci.&Tech. Chongqing Univ. of Post & Tele. Chongqing

This paper introduces a new algorithm for remote sensing image edge detection based on fuzzy *** of the complexity, the highly consistency of edges and the evidence of noise in remote sensing image, this algorithm links the mathematical morphology, the method of slipping window and fuzzy enhancing to extract the information of edges. At the beginning of the process in the proposed algorithm, the edges in the slipping windows are enhanced by using the method of fuzzy *** the slipping window traverses the whole ***, it detects the edges of remote sensing image by mathematical morphology operators. The simulations in this paper prove that this algorithm which contains many advantages of some kinds of methods not only is able to solve the problem by using single method, but also can elevate the edges and keep the image sharp at the same time.

关键词： Remote sensing image edge detection Fuzzy sets Morphology Educational institutions image processing Object detection Information technology Application software Automation

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A novel image edge detection method using Linear Prediction

A novel image edge detection method using Linear Prediction

引用

Midwest Symposium on Circuits and Systems (MWSCAS)

作者： James Z. Zhang Peter C. Tay Robert D. Adams Department of Engineering and Technology The Kimmel School Western Carolina University Cullowhee NC USA

Traditionally, Linear Prediction is used to predict future values of a signal using past values. The goal is to minimize prediction errors. In this paper, we propose a novel method of utilizing prediction errors to extract edges of images. In this method, smooth prediction errors are minimized while steep changes (larger errors) are amplified. Therefore, when applied to image edge detection, edge information can be accurately extracted. The proposed method is compared with predominant methods such as Sobel and Canny methods. While there is no mathematical proof that the proposed method outperforms predominant methods, however, examples presented in this paper may suggest that the proposed method may perform better for certain applications.

关键词： image edge detection Data mining Nonlinear filters Computer errors Linear predictive coding Equations Filtering Speech processing Feature extraction Text recognition

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An Improved Method for image edge detection Based on GM(1,1) Model

An Improved Method for Image Edge Detection Based on GM(1,1)...

引用

International Conference on Artificial Intelligence and Computational Intelligence (AICI)

作者： Jianxin Zhang Lang Wu College of Mechanical Engineering and Automation Zhejiang Science and Technology University Hangzhou China

The GM(1,1) model usually uses the first component of the first order accumulated generating operation(AGO) sequence X(1) as the initial condition to model in the research and application of image edge detection. This model has the disadvantage of being unable to completely utilize the latest information. Also it can't detect out all edge points because it detects the image only on two directions of horizontal and vertical. So in this paper, an improved GM(1,1) model is proposed for edge detection. It uses the last component of sequence X(1) as the initial condition of GM(1,1) model and predicts the pixel value on eight directions. Then the predicted image is subtracted by the original image to find out the position points with hopping grey values, which are edge points. Experimental results show that this algorithm can effectively detect out a complete image edge.

关键词： image edge detection Predictive models image processing Data mining Pixel Artificial intelligence Computational intelligence Educational institutions Mechanical engineering Automation

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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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Performance enhancement in image edge detection technique

Performance enhancement in image edge detection technique

引用

International Conference on Signal and Information Processing (IConSIP)

作者： Anil Patel Amrut Patel Electronics and Communication Department Ganpat University Mehsana India

ISBN: (纸本)9781509015238

edges are instant change in intensity value of pixels in the digital image. image edge detection converts original image in to binary image. This binary image contains information about edges of digital image. Recently Ant Colony Optimization Meta-heuristic algorithm is used for the image edge detection. Ant colony optimization algorithm is inspired from the behaviour of real ants. From this ACO based algorithm we get pheromone matrix at end, which contains the information about edge pixels of original image. Discrete wavelet transform is used to decompose original image in for sub-bands. ACO algorithm is separately applied on that four sub-bands and reconstructed image of these four components give better result than single ACO edge detected image. Dual tree complex wavelet transform is advance than discrete wavelet transform. Problems in DWT like overemphasized, distortion and less visible image are removed using DT-CWT with ACO algorithm. It has higher orientation property. K-means clustering algorithm and Fuzzy C-means algorithms are used to decide whether pixels in image are edge or not. So that proposed algorithms which are ACO + DT-CWT with K-means clustering algorithm and Fuzzy C-means algorithm, they are able to find all possible edges from image and give better result compared to other edge detection algorithms.

关键词： image edge detection Clustering algorithms Ant colony optimization Discrete wavelet transforms Signal processing algorithms Digital images

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Vector-valued color image edge detection using Green function approach

Vector-valued color image edge detection using Green functio...

引用

Iranian Machine Vision and image Processing (MVIP)

作者： Zahra Zareizadeh Reza P. R. Hasanzadeh Gholamreza Baghersalimi DSP Research Laboratory Department of Electrical Engineering University of Guilan Rasht Iran

In this paper, an extended version of differential equations is introduced on the concept of edge detection methods for color images based on the correlation of R, G, and B components. To obtain the color edge detection operator, the Green's function approach is used to derive the obtained differential equation. The proposed color edge detection method is compared with other color edge detection methods on the several test images. The experimental results show the feasibility of the proposed approach.

关键词： image edge detection image color analysis Color Green function Detectors Equations Pixel

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Research on image edge detection based on wavelet transform algorithm

Research on image edge detection based on wavelet transform ...

引用

International Conference on Test and Measurement (ICTM)

作者： Chenggang Zhen Yingmei Su Network Administration Center North China Electric Power University Baoding China College of Computer Science and Technology North China Electric Power University Baoding China

ISBN: (纸本)9781424446995

image edge detection has always been a hot research in the field of image processing. This article describes several classical detection algorithms and wavelet transform algorithm, analysis and compares the experimental *** results show that the wavelet transform algorithm can effectively detect the image edge, superior to the traditional edge detection algorithm.

关键词： image edge detection Wavelet transforms Wavelet analysis Laplace equations Testing image analysis Algorithm design and analysis image processing Convolution Filtering

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