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A Novel Hardware Solution for Efficient Approximate Fuzzy image edge detection

IEEE TRANSACTIONS ON FUZZY SYSTEMS 2024年第5期32卷 3199-3210页

作者： Behbahani, Fereshteh Jooq, Mohammad Khaleqi Qaleh Moaiyeri, Mohammad Hossein Azghadi, Mostafa Rahimi Shahed Univ Dept Elect & Elect Engn Tehran *** Iran Inje Univ Ctr Nano Mfg Dept Nanosci & Engn Gimhae 50834 South Korea Shahid Beheshti Univ Fac Elect Engn Tehran *** Iran James Cook Univ Coll Sci & Engn Townsville Qld 4811 Australia

In practical fuzzy applications, such as image processing, the utilization of precise models in hardware may not be the most efficient approach due to increased energy consumption and chip resource allocation. In a fuzzy system, an approximate implementation of min-max blocks offers an efficient solution with minimal accuracy compromise. Nevertheless, recent designs predominantly employ noncommercialized technologies for the fundamental fuzzy blocks. This article introduces a novel hardware solution for approximate fuzzy image edge detection using the well-established independent gate Fin field-effect transistor (FinFET) technology. The proposed hardware leverages two inference rules to identify edge pixels effectively. The fuzzy inference engine is implemented at the circuit level using 24 FinFETs, whereas the defuzzifier section incorporates four FinFETs with a configurable thresholding structure for optimal performance. Our circuit-level simulations reveal a remarkable 71% reduction in energy consumption compared with previous designs. The edge detection results are compared at the system level with the MATLAB Sobel edge detector. The proposed approximate hardware consistently matches the Sobel edge detection outcomes, exhibiting a 15% average improvements in data loss rate than other approximate structures. A figure of merit (FoM) is introduced to provide a comprehensive evaluation, considering both circuit and system-level metrics. The proposed FinFET-based hardware outperforms other approximate and even exact fuzzy edge detection hardware designs, boasting a 1.8 times higher FoM. This design paradigm exemplifies a promising direction toward compact and energy-efficient on-chip hardware implementations of real-world fuzzy systems.

关键词： Approximate fuzzy hardware Fin field-effect transistor (FinFET) image edge detection min-max circuits

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A novel digital fuzzy system for image edge detection based on wrap-gate carbon nanotube transistors

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COMPUTERS & ELECTRICAL ENGINEERING 2020年 87卷 106811-106811页

作者： Bozorgmehr, Ali Jooq, Mohammad Khaleqi Qaleh Moaiyeri, Mohammad Hossein Navi, Keivan Bagherzadeh, Nader Shahid Beheshti Univ Dept Comp Sci & Engn Tehran Iran Shahid Beheshti Univ Nanotechnol & Quantum Comp Lab Tehran Iran Shahid Beheshti Univ Fac Elect Engn Tehran Iran Univ Calif Irvine Dept Elect Engn & Comp Sci Irvine CA USA

This study presents a novel digital fuzzy approach for image edge detection based on carbon nanotube field effect transistor (CNTFET). The proposed design employs a simple fuzzy rule for digital image edge detection. To investigate the functionality and performance of the proposed fuzzy approach, our results are compared with the MATLAB edge detection operators such as Sobel, Canny, and Prewitt. Based on the simulation results, we demonstrate that the proposed fuzzy approach can be implemented through nanoscale logic gates and provide a reasonable accuracy. The core element of the proposed fuzzy system, implemented with CNTFETs, occupies 0.22 mu m(2) layout area and consumes 535 nW power consumption. Our results also emphasize the benefits of the Gate-All-Around (GAA) CNTFETs as a potential candidate for nanoscale digital fuzzy image processing applications.

关键词： Logic gates CNTFET fuzzy system image edge detection Fuzzy logic

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Multiscale Anisotropic Morphological Directional Derivatives for Noise-Robust image edge detection

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IEEE ACCESS 2022年 10卷 19162-19173页

作者： Yu, Xiaohang Wang, Xinyu Liu, Jie Xie, Rongrong Li, Yunhong Xian Polytech Univ Sch Elect & Informat Xian 710048 Peoples R China

Different types of noise interference lead to low accuracy of image edge detection and severe loss of feature extraction details. A new noise-robust edge detection method is proposed, which uses a set of multiscale anisotropic morphological directional derivatives to extract the edge map of an input image. The main advantage of the method is that high edge resolution is maintained while reducing noise interference. The following five parts form the whole framework of this paper. First, multiscale anisotropic morphologic directional derivatives (MSAMDDs) are proposed to filter and obtain the local gray value of the image. Second, the edge strength map (ESM) is extracted by using spatial matching filters. In the third stage, multiscale edge direction maps (EDMs) based on the directional matched filters are fused, and the new EDM is constructed. Fourth, edge contours are obtained by embedding the ESM and the EDM into the standard route of Canny detection. Finally, the precision-recall curve and Pratt's figure of merit (FOM) are used to evaluate the proposed method against eight state-of-the-art methods on three data sets. The experimental results show that the proposed method can perform better for noise-free (F-measure value of 0.776) and Gaussian noise (FOM value of 95.75%) and attains the best performance in impulse noise images (highest FOM value of 98.90%).

关键词： image edge detection Noise robustness Feature extraction Gray-scale Detectors Spatial resolution Licenses edge detection anisotropic morphological directional derivatives multiscale ground truth

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A new construction of an image edge detection mask based on Caputo-Fabrizio fractional derivative

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VISUAL COMPUTER 2021年第6期37卷 1545-1557页

作者： Aboutabit, N. Sultan Moulay Slimane Univ ENSA Khouribga IPIM Lab POB 523 Beni Mellal 23000 Morocco

In recent years, the research on image processing based on fractional calculus has attracted much attention. In this work, we proposed a new way to construct an image edge detection mask based on the fractional-order derivative using the Caputo-Fabrizio formulation. The proposed mask was experimented on a large dataset of natural images in both noiseless and noisy situations. In comparison with both classical and fractional edge detectors, the achieved results demonstrated the advantageous performances of the proposed edge detector.

关键词： image edge detection Fractional-order derivative Caputo-Fabrizio Non-singular kernel

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Rotation Feature Extraction for Moving Targets Based on Temporal Differencing and image edge detection

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IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 2016年第10期13卷 1512-1516页

作者： Li, Zhangfeng Zhao, Guoqiang Li, Shiyong Sun, Houjun Tao, Ran Huang, Xiaojing Guo, Y. Jay Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Univ Technol Sydney Global Big Data Technol Ctr Sydney NSW 2007 Australia

A rotation parameter extraction method based on temporal differencing and image edge detection from range-Doppler images is presented in this letter. The proposed method first detects the motion trail of the moving pixels caused by the rotating parts in temporal differential range-Doppler images using image edge detection. A Doppler-slow-time image is then generated from the edge pixels on the motion trail. Finally, the rotation parameters are extracted from the Doppler-slow-time image. The proposed method is simple, rapid, and practical. Computer simulations and experimental results demonstrate its effectiveness in terms of computation time compared with existing methods.

关键词： image edge detection micro-Doppler range-Doppler image rotation target temporal differencing

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Research on the improvement of image edge detection algorithm based on artificial neural network

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OPTIK 2015年第21期126卷 2974-2978页

作者： Gu, Jinan Pan, Yuelong Wang, Hongmei Jiangsu Univ Mech Informat Res Ctr Zhenjiang 212013 Jiangsu Peoples R China Mech Informat Engn Technol Res Ctr Zhenjiang Zhenjiang 212013 Jiangsu Peoples R China

image edge detection is an essential basis of computer vision that has made rapid progress these years. Given the importance of the edge detection and the maturity of ANN (artificial neural network), we provide a research paper on the algorithms of image edge detection based on ANN. Firstly, we review the classic methods of edge detection and introduce some new methods proposed these years. Secondly, the foundations of ANN are briefly introduced. Subsequently, we present a traditional edge detection method based on ANN and summarize some disadvantages of this method. Finally, a new edge detection method based on ANN and parallel computing is put forward. The new method is superior to the old one in the efficiency and accuracy of detection. (C) 2015 Elsevier GmbH. All rights reserved.

关键词： image edge detection Artificial neural network Parallel computing Dynamic window

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Data Efficient Digital Micromirror Device-Based image edge detection Sensor Using Space-Time Processing

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IEEE SENSORS JOURNAL 2012年第5期12卷 1043-1047页

作者： Riza, Nabeel A. Marraccini, Philip J. Baxley, Cody R. Natl Univ Ireland Univ Coll Cork Dept Elect & Elect Engn Cork Ireland Natl Univ Ireland Univ Coll Cork Tyndall Natl Inst Cork Ireland Draper Lab Cambridge MA 02139 USA

This paper presents a novel optical image scene object boundary mapping sensor using combined space-time processing within the framework of a Digital Micromirror Device (DMD). Sensor operation data efficiency is generated by smart spatial scanning of the image plane combined with single-pixel basis time delay electronic processing. In effect, compressed sensing is achieved using a hybrid optical-electronic means. Experimental results for target boundary detection are demonstrated for visible light illuminated rectangular and a multi-square shaped targets. The presented remote imaging sensor is ideal for use in environments where brightly illuminated or radiating objects require shape-detection imaging within hazardous extreme environments of radiation, heat, cold, and harmful machine parts.

关键词： image edge detection optical imaging

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Flash-based in-memory computing for stochastic computing in image edge detection

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Journal of Semiconductors 2023年第5期44卷 145-149页

作者： Zhaohui Sun Yang Feng Peng Guo Zheng Dong Junyu Zhang Jing Liu Xuepeng Zhan Jixuan Wu Jiezhi Chen School of Information Science and Engineering(ISE) Shandong UniversityQingdao 266000China Shandong Sinochip Semiconductors Co.Ltd Jinan 250101China Neumem Co. LtdHefei 230088China Key Laboratory of Microelectronic Devices and Integrated Technology Institute of Microelectronics of Chinese Academy of SciencesBeijing 100029China

The“memory wall”of traditional von Neumann computing systems severely restricts the efficiency of data-intensive task execution,while in-memory computing(IMC)architecture is a promising approach to breaking the *** variations and instability in ultra-scaled memory cells seriously degrade the calculation accuracy in IMC architectures,stochastic computing(SC)can compensate for these shortcomings due to its low sensitivity to cell ***,massive parallel computing can be processed to improve the speed and efficiency of the *** this paper,by designing logic functions in NOR flash arrays,SC in IMC for the image edge detection is realized,demonstrating ultra-low computational complexity and power consumption(25.5 fJ/pixel at 2-bit sequence length).More impressively,the noise immunity is 6 times higher than that of the traditional binary method,showing good tolerances to cell variation and reliability degradation when implementing massive parallel computation in the array.

关键词： in-memory computing stochastic computing NOR flash memory image edge detection

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SAR image edge detection With Recurrent Guidance Filter

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IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 2021年第6期18卷 1064-1068页

作者： Jing, Wenbo Jin, Tian Xiang, Deliang Natl Univ Def Technol Coll Elect Sci & Technol Changsha 410073 Peoples R China Sci & Technol Near Surface Detect Lab Wuxi 214035 Jiangsu Peoples R China Natl Innovat Inst Technol Beijing 100091 Peoples R China

While traditional edge detectors concentrate on modifying the shape of the window function, we consider the edge detection problem from a new perspective, and an effective recurrent guidance filter is proposed in this letter. The proposed filter is elaborately designed for edge detection tasks and aims to remove the nonedge information including speckle noise and detailed texture and preserve edge information simultaneously. We first filter the image by the proposed filter and a filtered image is obtained. Then, by using the edge detector with the Gaussian-shaped window, which was previously proposed by us and performing the postprocessing method, the edge response is extracted from the filtered image. Both objective and subjective experimental results on simulated and real synthetic aperture radar (SAR) images demonstrate that the edge detector based on the recurrent guidance filter yields better performance than the state-of-the-art edge detectors.

关键词： image edge detection Detectors Microsoft Windows Synthetic aperture radar Speckle Shape Radar imaging edge detection ratio-based edge detector recurrent guidance filter synthetic aperture radar (SAR) image

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image edge detection based on nonsubsampled contourlet transform and mathematical morphology

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Journal of Southeast University(English Edition) 2012年第4期28卷 445-450页

作者：何坤贤王庆肖彦昌王晓兵东南大学仪器科学与工程学院南京210096 南京炮兵学院射击教研室南京211132

A novel algorithm for image edge detection is presented. This algorithm combines the nonsubsampled contourlet transform and the mathematical morphology. First, the source image is decomposed by the nonsubsampled contourlet transform into multi-scale and multi-directional subbands. Then the edges in the high-frequency and low-frequency sub-bands are respectively extracted by the dualthreshold modulus maxima method and the mathematical morphology operator. Finally, the edges from the high- frequency and low-frequency sub-bands are integrated to the edges of the source image, which are refined, and isolated points are excluded to achieve the edges of the source image. The simulation results show that the proposed algorithm can effectively suppress noise, eliminate pseudo-edges and overcome the adverse effects caused by uneven illumination to a certain extent. Compared with the traditional methods such as LoG, Sobel, and Carmy operators and the modulus maxima algorithm, the proposed method can maintain sufficient positioning accuracy and edge details, and it can also make an improvement in the completeness, smoothness and clearness of the outline.

关键词： image edge detection nonsubsampled contourlet transform ( NSCT ) modulus maxima dual-threshold mathematical morphology structural elements

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