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检索条件"主题词=Image Edge detection"

共 27915 条记录，以下是61-70 订阅

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image edge detection using adaptive morphology Meyer wavelet-CNN

Image edge detection using adaptive morphology Meyer wavelet...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Young-Hyun Baek Oh-Sung Byun Sung-Rung Moon Department of Electronic Engineering Wonkwang University Iksan Chungbuk South Korea

ISBN: (纸本)0780378989

The boundary of an object image in a digital image is distorted by noise or other elements of the system that mix with the image during transmission. In this paper, it is proposed that the object boundary be detected and exactly divided for optimal edge detection method. After bringing up the object boundary by applying adaptive morphology on the threshold of the input image, the optimal edge is detected using wavelet-cellular neural network (CNN). The proposed method is compared with the conventional Sobel method used as an edge detection algorithm. The proposed algorithm is confirmed to be superior than the conventional methods.

关键词： image edge detection Morphology Cellular neural networks image processing Digital images Nonlinear distortion Signal processing Moon Cellular networks Neural networks

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image edge detection based on statistical features

Image edge detection based on statistical features

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International Conference on Intelligent Computing and Integrated Systems (ICISS)

作者： Zhi-yong Peng Hong-zhou Li Jian-ming Liu Guilin University of Electronic and Technology Guilin Guangxi China

Classical edge detection method has great limitation, because the noise contained in the image has significant influence on the results, while the speed of edge detection and whether the edge can be detected or not are also the concerned problems. This paper proposed two edge detection methods based on the statistical features, which can accurately detect the edges and suppress the impact of the noise on the results, while the edge has a good consistency. Extensive testing results have shown great potential on our novel method.

关键词： image edge detection Integrated optics Optical noise Noise

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image edge detection and segmentation based on the Hilbert transform

Image edge detection and segmentation based on the Hilbert t...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： G.M. Livadas A.G. Constantinides Department of Electrical Engineering Imperial College London London UK

An efficient edge detection model based on a two-stage procedure is presented. The first stage consists of a linear transformation of an artificially created signal that has the property of detecting step edges irrespective of the distribution of the intervals between two consecutive edges. It is demonstrated that the Hilbert transform possesses this property and also outperforms the derivative operation in the detection of step edges in the presence of noise. The second stage consists of an appropriate mapping of the filtered results into edge detection primitives. Practical confirmation of the results is given by means of examples.< >

关键词： image edge detection image segmentation Nonlinear filters Detectors Educational institutions Maximum likelihood detection Mechanical factors Random processes Additive noise Noise shaping

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image edge detection Based on FPGA

Image Edge Detection Based on FPGA

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

作者： Zhengyang Guo Wenbo Xu Zhilei Chai School of Information Technology Jiangnan University Wuxi China

Field Programmable Gate Array (FPGA) is an effective device to realize real-time parallel processing of vast amounts of video data because of the fine-grain reconfigurable structures. This paper presents a kind of parallel processing construction of Sobel edge detection enhancement algorithm, which can quickly get the result of one pixel in only one clock periods. The algorithm is designed with a FPGA chip called XC3S200- 5ft256, and it can process 1024×1024×8 Gray Scale image successfully. The design can locate the edge of the gray image quickly and efficiently.

关键词： image edge detection Field programmable gate arrays Kernel Pixel Convolution Real time systems

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image edge detection with discretely spaced FitzHugh-Nagumo type excitable elements

Image edge detection with discretely spaced FitzHugh-Nagumo ...

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International Workshop on Nonlinear Dynamics and Synchronization, INDS

作者： Atsushi Nomura Makoto Ichikawa Koichi Okada Hidetoshi Miike Tatsunari Sakurai Yoshiki Mizukami Yamaguchi University Yamaguchi Japan Faculty of Letters Chiba University Japan Education Promotion Center Yamaguchi University Japan Graduate School of Science and Engineering Yamaguchi University Japan Graduate School of Science Chiba University Japan

This paper presents a computer algorithm of detecting edges from a grey scale image with FitzHugh-Nagumo type excitable elements discretely spaced at image grid points. A previous edge detection algorithm utilising the elements is not applicable to darker intensity areas surrounded by brighter ones; the algorithm fails in detecting edges in the areas. In order to solve the problem in detecting edges in relatively dark areas, we proposed to utilise an intensity inverted image as well as its original one. The proposed algorithm firstly provides a tentative edge map from the original image, and simultaneously provides an additional tentative edge map from the inverted image. Then, the algorithm provides a final edge map by merging the two edge maps. We quantitatively confirm performance of the proposed algorithm, in comparison with that of the previous one and that of the Canny algorithm for an artificial grey scale image not having noise. We furthermore confirm robustness and convergence of the proposed algorithm for a noisy image and real ones. These results shows that the performance of the proposed algorithm is much higher than the previous one and is comparable with the Canny algorithm for a noise-less image, and the proposed algorithm converges for all of the images. However, the proposed algorithm is vulnerable for additive noise, in comparison with the Canny algorithm and the anisotropic diffusion algorithm.

关键词： image edge detection detection algorithms Equations Educational institutions Anisotropic magnetoresistance Copper

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image edge detection of wood defects based on multi-fractal analysis

Image edge detection of wood defects based on multi-fractal ...

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IEEE International Conference on Automation and Logistics

作者： Hongbo Mu Dawei Qi Mingming Zhang Lei Yu Department of Physics Northeast Forestry University Harbin Heilongjiang China Department of Bioinformatics Harbin Medicine University Harbin Heilongjiang China

ISBN: (纸本)9781424425020

A reliable detection method for X-ray image of wood with defects based on the multi-fractal analysis was presented in the paper. Adopting singular Holder index and multi-fractal spectrum theory and computing the singular value and multi-fractal spectrum of each pixel point of image edges of wood defects in order that the images were identified easily. According to the experimental results, the given algorithm can reduce unimportant edge information, while it also keeps some important detail information of the image well by correction of the measure. It is useful and current method for image processing. This study lays a foundation for automatic recognition. It is significant for the modern wood processing and utilization.

关键词： Fractals image edge detection X-ray imaging Indexes Pixel image processing Computers

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image edge detection Method Based on Multi-Structure and Multi-Scale Mathematical Morphology

Image Edge Detection Method Based on Multi-Structure and Mul...

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International Conference on Multimedia Technology

作者： Jinlong Chen Bin Zhang Yingjian Qi Fei Jin Xuan Si School of Science Communication University of China Beijing China Dept. of Computer and Information Science Temple University Philadelphia USA Institute of Automation Chinese Academy of Sciences Beijing China

image edge detection plays an important role in the image processing, On the basis of studying mathematical morphology and morphological edge detection operator in the field of application of edge detection in depth and integrating morphological expansion and corrosion, an amended edge detection operator was proposed and used to detect the image edge. Then change the edge elements structure and scale. Integrating the edge characteristics under the structure and scale, the ideal image edge can be obtained under the conditions of noise .The simulation results demonstrate the feasibility and effectiveness of the operator.

关键词： image edge detection Noise Information entropy Morphology Gray-scale Mathematical model Equations

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image edge detection method based on the direction feature of fuzzy entropy

Image edge detection method based on the direction feature o...

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International Conference on Natural Computation (ICNC)

作者： Chun He Jun Lu Junwei Han School of Electrical and Electronic Engineering North China Electric Power University Beijing China

To improve the image edge detection capability, this paper presents an image edge detection method based on the direction feature of fuzzy entropy. Firstly, the proposed method operates the fuzzy membership function and fuzzy entropy function for achieving a neighborhood fuzzy entropy feature space from the image feature to enhance the fuzzy edge contrast, and defines twelve valid edge direction structures in the 3×3 neighborhood of the feature space. Then it extracts the valid direction structural information arrays of every pixel point, and combines the direction structure measurement arrays to make non-maxima suppression. Finally the proposed method implements an adaptive threshold to estimate and determine image edges. Experimental results illustrate that the proposed method has better performance in the image edge detection with more image detail information.

关键词： image edge detection Pixel Entropy Feature extraction Equations Data mining Mathematical model

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image edge detection method based on a simplified PCNN model with anisotropic linking mechanism

Image edge detection method based on a simplified PCNN model...

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International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Zhan Shi Jinglu Hu Graduate School of Information System and Production Waseda University Kitakyushu Japan

This paper presents a novel image edge detection method based on a simplified pulse coupled neural network with anisotropic interconnections (PCNNAI) by applying an anisotropic linking mechanism. PCNNAI utilizes the anisotropic linking mechanism to create an adaptive synaptic weight matrix to achieve the anisotropic interconnection model among neurons. Therefore, the neurons corresponding to edge and non-edge pixels will receive different feedback signal from neighborhood. Due to the PCNN structure the edges will be detected by different internal activity of edge neurons and non-edge neurons. Comparing with conventional PCNN edge detection methods, PCNNAI simplifies the system structure and the outputs are controllable, meanwhile PCNNAI also achieves more accurate results than the classical image edge detectors. Experimental results show that PCNNAI is effective at image edge detection.

关键词： image edge detection Neurons Joining processes Pixel Detectors Artificial neural networks Adaptation model

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image edge detection Based on a Spatial General Autoregressive Model

Image Edge Detection Based on a Spatial General Autoregressi...

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IEEE Information Technology and Mechatronics Engineering Conference (ITOEC)

作者： Fei Hao Ruwen Chen Fan Wang Delin Chen Jingjing Shi Yuntao Hu Key Laboratory of Rail Transit Equipment Nanjing Institute of Technology Nanjing China

ISBN: (纸本)9781538653746

A new scheme for image edge detection based spatial general autoregressive model (SGAR) is proposed in this work, which takes into consideration the nonlinearity at both edges and non-edges. First the SGAR model is derived which fuses both linear and non-linear spatial autoregressive model in one expression and whereafter the spatial relation of a lattice site with its neighbors is adaptively learnt by using a SGAR model with a robust parameter estimator named GM estimator. Then the edge image is produced by thresholding the residual image which is equal to the difference between the original image and the prediction image. Finally, experiments are carried out on a worldwide dataset to verify the feasibility of the proposed scheme. Experiment results also indicate that the future works need to be carried out to further improve practicability of the proposed scheme.

关键词： image edge detection Adaptation models Mathematical model Numerical models Predictive models Lattices Data models

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