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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 fusion of wavelet transform and mathematical morphology

Image edge detection based on fusion of wavelet transform an...

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International Conference on Computer Science and Education

作者： Hong-xin Zhang Jing-yao Li Ming-zhu Wang He Li Intelligent Machine Institute Harbin University of Science and Technology

ISBN: (纸本)9781509022199

In order to realize the leading role of machine vision in intelligent cargo handling of the robot, a fusion method of visual image edge detection based on wavelet transform and mathematical morphology is proposed. That wavelet transform is used for image edge detection exists missing detection, smoothness and weak edge problem. So an improved method needs to be studied, in which a wavelet transform and improved mathematical morphology are respectively used to extract the edge of the original image, and then a fusion of two methods is done to obtain a better edge detection after threshold processing. Comparing the proposed algorithm with several classical edge detection algorithms, the experimental result shows that edge detection method proposed in this paper can effectively reduce the influence of noise and to a certain extent enhance the weakening edge, improve the accuracy of the image detection.

关键词： Machine vision image edge detection Wavelet transform Mathematical morphology

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image edge detection based on wavelet transform and Canny operator

Image edge detection based on wavelet transform and Canny op...

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International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

作者： Cai-Xia Deng Ting-Ting Bai Ying Geng Applied Science College Harbin University of Science and Technology Harbin China

A method for image edge detection based on image fusion is presented in this paper. Since traditional wavelet transforms are unable to control the noise well and the edge is not consistent with direction properties, some improvements are made and a new kind of wavelet transform is proposed. It detects the edge of original image by means of new wavelet transform and Canny operator respectively, then produces a new image by fusing and analyzing the two results based on the experimental results. It is shown that the proposed method provides clearer and smoother edges than that using Sobel or wavelet transformation algorithms alone. This algorithm is simple, useful and easy to implement.

关键词： image edge detection Wavelet transforms Wavelet analysis Continuous wavelet transforms image analysis Pattern analysis Pattern recognition Fourier transforms Educational institutions image fusion

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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 Based on Interval Type-2 Fuzzy Similarity

Image Edge Detection Based on Interval Type-2 Fuzzy Similari...

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Electronic Information Technology and Computer Engineering (EITCE), International Conference on

作者： Lili Tang Jialiang Xie Mingzhi Chen Chunyao Xu Rui Zhang College of Science Jimei University Xiamen P. R. China Beika Technology Limited Company Xiamen P. R. China

ISBN: (数字)9781728135847

ISBN: (纸本)9781728135854

This paper presents a new method for edge detection of color images that is based on interval type-2 fuzzy similarity. Firstly, the noise of the image is estimated, and the image with noise higher than the threshold value is filtered out. Then this paper combines the type-2 fuzzy set theory to calculate the adjacent pixel similarity of each channel pixels in the image. After type reduction, it is divided into the edge and non-edge pixels by threshold. Compare to Sober operator, Canny operator, LOG operator and type-1 fuzzy similarity, the proposed method has a great balance noise resistance and edge detection accuracy.

关键词： image edge detection Fuzzy sets Estimation Filtering theory Noise level Wiener filters image color analysis

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image edge detection Based on Neighborhood Limited EMD Method and Lifting Wavelet Transform

Image Edge Detection Based on Neighborhood Limited EMD Metho...

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International Conference on Multimedia Technology

作者： Guangqiong Li Jiafu Jiang College of Computer and Electronic Engineering Hunan University of Commerce ChangSha China School of Computer and Communication Engineering Changsha University of Science and Technology Changsha China

An effective algorithm of image edge detection based on neighborhood limited empirical mode decomposition and lifting wavelet analysis is presented. The image signal is decomposed to a number of intrinsic mode function(IMF) function via neighborhood limited empirical mode decomposition(EMD), then each IMF function is processed by lifting wavelet transform. The application of this method to image shows that it is effective and practical.

关键词： Wavelet transforms image edge detection Wavelet analysis Algorithm design and analysis image reconstruction Pixel

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Gray-scale image edge detection Based on directional Beamlet Transform

Gray-scale Image Edge Detection Based on directional Beamlet...

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9th International Conference on Signal Processing

作者： Wang Min Zhang Yanning NW Polytech Univ Sch Comp Xian 710072 Peoples R China

ISBN: (纸本)9781424421787

Traditional edge defectors based on pixel processing one by one have poor ability to detect edge in noisy images. The beamlet transform is a method of linear feature detection but fail to detect edge. The directional beamlet transform is proposed in this paper. The DBT transfer the linear singularity to point-singularity, and reduce the influence to edge of noise. Experiment results prove the efficiency of the method proposed even in noisy images.

关键词： Gray-scale image edge detection image segmentation Discrete transforms Pixel Detectors Dictionaries Computer vision Military computing Joining processes

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Multi-scale Shaft Parts' image edge detection and Measurement based on Wavelet Transform

Multi-scale Shaft Parts' Image Edge Detection and Measuremen...

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Pacific/Asia Workshop on Computational Intelligence and Industrial Application

作者： Ge Ji Wang Yaonan Zhou Bowen Zhang Hui Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China

ISBN: (纸本)9781424442041

Multi-scale edge detection method was demonstrated, also detailed algorithms, flow chart were put forward, shaft parts' image as an example in this article. The algorithms resolve two problems existing in the first generation multi-scale edge detection, the demerits were edge defined only considering its irregularity and difficult selection of filtering scale. More satisfied edge detection results can be got applying wavelet transformations' regularity under different scales or the same scale. To realize image measurement, system calibration is the key factor, which ascertains the detection accuracy. detection experiments are carried out to compare between the traditional operators and proposed algorithm, real dimension lengths of the shaft parts are calculated with the calibrated coefficient.

关键词： Shafts image edge detection Wavelet transforms Filtering algorithms Smoothing methods image color analysis image texture analysis Conferences Computational intelligence Computer industry

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A digitalization-based image edge detection algorithm in intelligent recognition of 5G smart grid

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EXPERT SYSTEMS WITH APPLICATIONS 2023年第1期233卷

作者： Tang, Pei Univ Coll London UCL Elect & Elect Engn Dept London England Univ Coll London UCL Gower St London WC1E 6BT England

In the 5G smart grid, battery liquid leakage negatively affects the safe storage and transportation of electricity. image edge detection help locate the liquid leakage phenomenon. This paper proposes a digitalization-based algorithm that converts the image to the codeword and judges the edge by the code weight. Its main steps are image sampling, quantization, coding and judging. Compared with traditional Sobel and Canny operators, the algorithm dramatically enhances detection ability with machine learning. Moreover, this paper applies the algorithm to detect the leakage of infrared battery images in the 5G smart grid;The results show that it can accurately extract the liquid leakage location, improving fault diagnosis and early risk warning.

关键词： 5G smart grid image edge detection Digitization Intelligent recognition Infrared images

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Spin device-based image edge detection architecture for neuromorphic computing

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NANOTECHNOLOGY 2024年第5期35卷 055201-055201页

作者： Verma, Gaurav Soni, Sandeep Kaushik, Brajesh Kumar Indian Inst Technol Roorkee Dept Elect & Commun Engn Roorkee 247667 Uttarakhand India NSEZ Cadence Design Syst Noida 201307 India

Artificial intelligence and deep learning today are utilized for several applications namely image processing, smart surveillance, edge computing, and so on. The hardware implementation of such applications has been a matter of concern due to huge area and energy requirements. The concept of computing in-memory and the use of non-volatile memory (NVM) devices have paved a path for resource-efficient hardware implementation. We propose a dual-level spin-orbit torque magnetic random-access memory (SOT-DLC MRAM) based crossbar array design for image edge detection. The presented in-memory edge detection algorithm framework provides spin-based crossbar designs that can intrinsically perform image edge detection in an energy-efficient manner. The simulation results are scaled down in energy consumption for data transfer by a factor of 8x for grayscale images with a comparatively smaller crossbar than an equivalent CMOS design. DLC SOT-MRAM outperforms CMOS-based hardware implementation in several key aspects, offering 1.53x greater area efficiency, 14.24x lower leakage power dissipation, and 3.63x improved energy efficiency. Additionally, when compared to conventional spin transfer torque (STT-MRAM and SOT-MRAM, SOT-DLC MRAM achieves higher energy efficiency with a 1.07x and 1.03x advantage, respectively. Further, we extended the image edge extraction framework to spiking domain where ant colony optimization (ACO) algorithm is implemented. The mathematical analysis is presented for mapping of conductance matrix of the crossbar during edge detection with an improved area and energy efficiency at hardware implementation. The pixel accuracy of edge-detected image from ACO is 4.9% and 3.72% higher than conventional Sobel and Canny based edge-detection.

关键词： computing-in-memory spintronics image edge detection

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