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International Conference on Intelligent Human-Machine Systems and Cybernetics

作者： Wang, Xiu-bi Sichuan Univ Sci & Engn Zigong Sichuan Peoples R China

ISBN: (纸本)9780769537528

The current widely used edge detection algorithm have Sobel, Roberts, Laplacian etc. The core idea of these algorithms is that the edge points correspond to the local maximal points of original image's gray-level gradient. However, when there are noises in images, these algorithms are very sensitive to noises, and may detect noise points as marginal points, and the real edge may not be detected because of the noises' interference. Designing image edge detection systems with good nature is a goal which all researchers pursue. Method of lifting can best deal with based on MRA Multi-resolution Analysis method which is time and memory consuming which impedes its real-time application. The process of lifting method was introduced. Method of image edge detection based on lifting wavelet was introduced. The algorithm, traditional wavelet image edge detection algorithms and canny operator are compared. Result of the experiment indicate, the quality of image have been improved. It is better than traditional wavelet and canny operator image edge detection algorithms.

关键词： Wavelet Transform lifting wavelet image edge detection

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Machine learning algorithm partially reconfigured on FPGA for an image edge detection system

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Journal of Electronic Science and Technology 2024年第2期22卷 48-68页

作者： Gracieth Cavalcanti Batista Johnny Oberg Osamu Saotome Haroldo F.de Campos Velho Elcio Hideiti Shiguemori Ingemar Soderquist Division of Electronic and Embedded Systems KTH Royal Institute of TechnologyStockholm 16440Sweden Electronic Engineering Division Aeronautics Institute of TechnologySao Josédos Campos SP 12228-900Brazil Laboratory of Applied Computing and Mathematics National Institute for Space ResearchSao Josédos Campos SP 12227-900Brazil Department of C4ISR Institute of Advanced StudiesSao Josédos Campos SP 12228-001Brazil Saab AB Linkoping 58188Sweden

Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,*** key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for this process is to combine inertial navigation system sensor information with the global navigation satellite system(GNSS)***,some factors can interfere with the GNSS signal,such as ionospheric scintillation,jamming,or *** alternative method to avoid using the GNSS signal is to apply an image processing approach by matching UAV images with georeferenced *** a high effort is required for image edge *** a support vector regression(SVR)model is proposed to reduce this computational load and processing *** dynamic partial reconfiguration(DPR)of part of the SVR datapath is implemented to accelerate the process,reduce the area,and analyze its granularity by increasing the grain size of the reconfigurable *** show that the implementation in hardware is 68 times faster than that in *** architecture with DPR also facilitates the low power consumption of 4 mW,leading to a reduction of 57%than that without *** is also the lowest power consumption in current machine learning hardware ***,the circuitry area is 41 times *** with Gaussian kernel shows a success rate of 99.18%and minimum square error of 0.0146 for testing with the planning *** system is useful for adaptive applications where the user/designer can modify/reconfigure the hardware layout during its application,thus contributing to lower power consumption,smaller hardware area,and shorter execution time.

关键词： Dynamic partial reconfiguration(DPR) Field programmable gate array(FPGA)implementation image edge detection Support vector regression(SVR) Unmanned aerial vehicle(UAV) pose estimation

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DESIGN OF AN image edge-detection FILTER USING THE SOBEL OPERATOR

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IEEE JOURNAL OF SOLID-STATE CIRCUITS 1988年第2期23卷 358-367页

作者： KANOPOULOS, N VASANTHAVADA, N BAKER, RL DUKE UNIV DEPT ELECT ENGNDURHAMNC 27706

The architecture of the edge detector presented is highly pipeline to perform the computations of gradient magnitude and direction for the output image samples. The chip design is based on a 2- mu m, double-metal, CMOS technology and was implemented using a silicon compiler system in less than 2 man-months. It is designed to operate with a 10-MHz two-phase clock, and it performs approximately 200*10/sup 6/ additions/s to provide the required magnitude and direction outputs every clock cycle. The function of the chip has been demonstrated with a prototype system that is performing image edge detection in real time.< >

关键词： image edge detection Filters CMOS technology Clocks Computer architecture Detectors Pipelines High performance computing Chip scale packaging Silicon compiler

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PCNN double step firing mode for image edge detection (Mar, 10.1007/s11042-022-12725-2, 2022)

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MULTIMEDIA TOOLS AND APPLICATIONS 2022年第19期81卷 27215-27215页

作者： Deng, Xiangyu Yang, Yahan Zhang, Huan Ma, Yide Northwest Normal Univ Coll Phys & Elect Engn Lanzhou 730070 Gansu Peoples R China Lanzhou Univ Sch Informat Sci & Engn Lanzhou 730000 Gansu Peoples R China

Pulse-coupled Neural Network (PCNN) is a third-generation artificial neural network that requires no training. Neurons in PCNN have two pulse burst modes: firing mode and fire-extinguishing mode. A lot of research has been conducted on achieving image segmentation using the fire-extinguishing mode, yet remains deficient on the characteristics and applications of the firing mode. Through analysis of the firing process of PCNN, we find that the network that works only on the firing mode has the characteristic of image edge detection. Then, we give a mathematical expression for the neuron firing time, and, using the expression, propose an image edge detection algorithm based on the characteristic of PCNN double step firing. Then, we analyze the parameter constraints for achieving PCNN double step firing and provide a method for the self-adaptive setting of the network parameters. To achieve the best edge detection, we conduct mathematical analysis on the relationship between edge detection performance and neighbor coupling, and provide a neighbor template structure and the setting of its values. Our results show that the proposed algorithm can obtain smooth and unbroken single pixels edges, and has nice robustness and efficiency for various kinds of images.

关键词： Double step firing image edge detection Neighborhood template design Parameter constraint condition Working characteristics of PCNN

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Memristor Crossbar Array Based ACO For image edge detection

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NEURAL PROCESSING LETTERS 2020年第2期51卷 1891-1905页

作者： Yu, Yongbin Deng, Quanxin Ren, Liyong Tashi, Nyima Univ Elect Sci & Technol China Sch Informat & Software Engn Chengdu Sichuan Peoples R China Tibet Univ Sch Informat Sci & Technol Lhasa Peoples R China

Memristor provides an available way to design and deploy swarm intelligence. As a typical swarm intelligence algorithm, ant colony optimization is implemented by the memristor crossbar array to make image edge detection in this paper. Firstly, a non-linear voltage-controlled memristor model with a relaxation term is proposed. Then, an improved ant colony optimization with padding strategy is designed. Thirdly, a memristor crossbar array with external control circuits is designed to implement ant colony optimization for image edge detection, which offers high device density and parallel computing. In the course of ant colony optimization based image edge detection deployed by memristor crossbar array, the threshold to generating edges can be directly chosen as the mean of the final conductance matrix. On the one hand, experiment results show that more delicate edges can be detected by proposed method compared to holistically-nested edge detection based on neural networks. On the other hand, Figure of merit of proposed method is better than that of Sobel operator.

关键词： Memristor Ant colony optimization image edge detection Crossbar array

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Bearing Fault detection in ASD-Powered Induction Machine Using MODWT and image edge detection

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IEEE ACCESS 2022年 10卷 24181-24193页

作者： Avina-Corral, Victor De Jesus Rangel-Magdaleno, Jose Peregrina-Barreto, Hayde Manuel Ramirez-Cortes, Juan Inst Nacl Astrofis Opt & Electr Elect Dept Digital Syst Grp Puebla 72810 Mexico Inst Nacl Astrofis Opt & Electr Comp Dept Puebla 72810 Mexico

Today the industry depends on various types of three-phase induction machines, requiring operating at variable speeds to perform more complex processes. Therefore, it is vital to monitor their operation conditions to maintain the optimal efficiency of the processes they perform and avoid significant economic losses. The proposed work presents the design and development of a method for bearing damage detection based on Maximal Overlap Discrete Wavelet Transform and image processing for edge detection. Accuracies achieved with three types of damage exceed 90%. The signals for the test are acquired from seven different operating conditions for each type of damage. Supply comes from a power grid source and an adjustable speed drive. The Maximal Overlap Discrete Wavelet Transform is applied with different filtering levels to the three phases of the stator current, the magnitude of the filtered signals is acquired, a periodic two-dimensional array is generated and further smoothed by a Gaussian filter allowing the observation of patterns at the edges. Finally, the obtained images are scanned with a 2-D mask aiming to detect and count patterns associated to the fault detection process. Statistical analysis is performed over characteristic signatures obtained from the current magnitude of the three phases at different classes of damage and several mechanical load conditions.

关键词： Discrete wavelet transforms Vibrations Variable speed drives image edge detection Frequency modulation Fault detection Multiresolution analysis Bearing fault detection (BFD) edge detection (ED) induction machine (IM) maximal overlap discrete wavelet transform

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The construction of 2D rotationally invariant wavelets and their application in image edge detection

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INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING 2008年第1期6卷 65-82页

作者： Zeng, Li Ma, Rui Huang, Jianyuan Hunziker, P. R. Chongqing Univ Educ Minist China ICT Res Ctr Key Lab Optoelect Technol & Syst Chongqing 400044 Peoples R China Chongqing Univ Coll Math & Phys Chongqing 400044 Peoples R China Univ Basel Hosp CH-4031 Basel Switzerland

Construction of rotationally invariant 2D wavelets is important in image processing, but is difficult. In this paper, the discrete form of a 2D rotationally invariant wavelet is constructed by back- projection from a 1D symmetrical wavelet. Such rotationally invariant 2D wavelets allow effective edge detection in any direction. These wavelets are combined with the 2D directional wavelets for the use in non- maximum suppression edge detection. The resulting binary edges are characterized by finer contours, differential detection characteristics and noise robustness compared to other edge detectors in various test images. In particular, where. ne binary edges in noisy images are required, this novel approach compares favorably to the classical methods of Canny and Mallat with detection of more edges thanks to the implicit denoising properties and the full rotational invariance of the method.

关键词： 2D wavelet construction rotationally invariant back-projection image edge detection

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Color image edge detection Method Based on the Improved Whale Optimization Algorithm

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IEEE ACCESS 2023年 11卷 5981-5989页

作者： Liu, Dujin Zhou, Shiji Shen, Rong Luo, Xuegang Sichuan Univ Arts & Sci Sch Intelligent Mfg Dazhou 635000 Peoples R China Panzhihua Univ Sch Math & Comp Panzhihua 617000 Peoples R China

A high level of computation is required for edge detection in color images captured by unmanned aerial vehicles (UAVs) to address issues, such as noise, distortion, and information loss. Thus, an edge detection method for UAV-captured color images based on the improved whale optimization algorithm (WOA) is proposed in this study. In this method, the color image pixels are represented by quaternions, and the global random position variables and information exchange mechanism are introduced into the random walk foraging formula of the WOA. Further, a random disturbance factor is also introduced into the predator-prey formula of the spiral bubble net. The proposed improved WOA is then used to obtain the preliminary edge of the UAV-captured color image. An edge-point classification method using the radius of the shortest distance between the whale and the current global optimum in each iteration is presented to enhance a preliminary edge. The experimental results show that the proposed edge detection method has the advantages of strong denoising, fast speed, and good quality.

关键词： image edge detection Autonomous aerial vehicles Quaternions Whale optimization algorithms image color analysis Spirals Classification and purification edge detection quaternion unmanned aerial vehicle (UAV) whale optimization algorithm (WOA)

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Leveraging Negative Capacitance CNTFETs for image Processing: An Ultra-Efficient Ternary image edge detection Hardware

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2021年第12期68卷 5108-5119页

作者： Behbahani, Fereshteh Jooq, Mohammad Khaleqi Qaleh Moaiyeri, Mohammad Hossein Tamersit, Khalil Shahed Univ Dept Elect Engn Tehran *** Iran Shahid Beheshti Univ Nanotechnol & Quantum Comp Lab Tehran *** Iran Shahid Beheshti Univ Fac Elect Engn Tehran *** Iran Univ 8 Mai 1945 Guelma Dept Elect & Telecommun Guelma 24000 Algeria Univ 8 Mai 1945 Guelma Lab Inverse Problems Modeling Informat & Syst PIM Guelma 24000 Algeria

Recently, integrating ferroelectric materials with nanotransistors such as carbon nanotube field-effect transistors (CNTFETs) has opened new doors for demonstrating a new generation of ultra-miniature circuits and systems. Utilizing the negative differential resistance effect in negative capacitance CNTFETs (NC-CNTFETs) has spurred the efforts for designing ultra-compact ternary circuits and systems similar to their binary structures. This paper presents an ultra-efficient ternary image edge detection hardware using NC-CNTFET technology. The proposed hardware is endowed with a noise reduction circuitry to mitigate the noise effects. Using four 1 x 3 kernels and concatenating the image pixels, the proposed ternary hardware has been designed using only 50 transistors. The proposed ternary hardware at the circuit level shows, on average, 74% improvements regarding power delay-product (PUP) compared to the CNTFET-based counterparts. Our comprehensive simulations indicate that the proposed NC-CNTFET-based hardware shows a 40% improvement in data loss, 2.2 times improvement in performance ratio, and 1.14 times improvement in Pratt's figure-of-merit, respectively, compared to the related designs. Our results accentuate that the proposed NC-CNTFET-based ternary hardware is a breakthrough achievement in demonstrating ultra-efficient and noise-immune ternary image processing circuits beyond the conventional binary counterparts.

关键词： Ferroelectric negative capacitance NC-CNTFET ternary image processing noise reduction image edge detection

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An Integrated Method Using Linear Homotopy Parametric Value for Enhancing image edge detection

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IEEE ACCESS 2024年 12卷 107113-107118页

作者： Shivam Kumar Jha, S. Mohana, N. Vellore Inst Technol Sch Adv Sci Dept Math Chennai 600127 India

This study introduces an integrated convolutional mask method for enhancing edge detection in digital images by combining the linear homotopy parametric value (LHP) with classical edge detection operators. Our results, obtained from extensive experimentation and comparison with conventional MATLAB-based methods, demonstrate that the LHP-based method outperforms previous techniques in terms of reliability and structural accuracy. LHP is integrated to address issues of noise sensitivity and diverse image structures, highlighting the algorithm's improved performance across a range of images.

关键词： image edge detection Noise measurement Convolutional neural networks Sensitivity Matlab Mathematical models Kernel Convolution edge detection enhancement gradient based method LHP

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