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FPGA implementation of cost-effective robust canny edge detection algorithm

JOURNAL OF REAL-TIME IMAGE PROCESSING 2019年第4期16卷 957-970页

作者： Sangeetha, D. Deepa, P. Govt Coll Technol Dept Elect & Commun Engn Coimbatore 641013 Tamil Nadu India

Implementation of canny edge detection algorithm significantly outperforms the existing edge detection techniques in many computer vision algorithms. However, canny edge detection algorithm is complex, time-consuming process with high hardware cost. To overcome these issues, a novel canny edge detection algorithm is proposed in block level to detect edges without any loss. It uses sobel operator, approximation methods to compute gradient magnitude and orientation for replacing complex operations with reduced hardware cost, existing non-maximum suppression, block classification for adaptive thresholding and existing hysteresis thresholding. Pipelining is introduced to reduce latency. The proposed algorithm is implemented on Xilinx Virtex-5 FPGA and it provides better performance compared to frame-level canny edge detection algorithm. The synthesized architecture reduces execution time by 6.8% and utilizes less resource to detect edges of 512x512 image compared to existing distributed canny edge detection algorithm.

关键词： Image processing canny edge detection algorithm VLSI architecture FPGA Hardware-cost

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Research on image text recognition based on canny edge detection algorithm and k-means algorithm

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INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2022年第SUPPL 1期13卷 72-80页

作者： Wu, Fangsheng Zhu, Changan Xu, Jinxiu Bhatt, Mohammed Wasim Sharma, Ashutosh Anhui Business Vocat Coll Inst Informat Engn Hefei 231131 Anhui Peoples R China Univ Sci & Technol China Hefei 230026 Anhui Peoples R China Cent Univ Punjab Bathinda India Southern Fed Univ Inst Comp Technol & Informat Secur Southern Fed Dist Russia

The latest research in the field of recognition of image characters has led to various developments in the modern technological works for the improvement of recognition rate and precision. This technology is significant in the field of character recognition, business card recognition, document recognition, vehicle license plate recognition etc. for smart city planning, thus its effectiveness should be improved. In order to improve the accuracy of image text recognition effectively, this article uses canny algorithm to process edge detection of text, and k-means algorithm for cluster pixel recognition. This unique combination combined with maximally stable extremal region and optimization of stroke width for image text yields better results in terms of recognition rate, recall, precision, F-score and accuracy. The results show that the correct recognition rate is 88.3% and 72.4% respectively with an accuracy value of 90.5% for the proposed method. This algorithm has high image text recognition rate, can recognize images taken in complex environment, and has good noise removal function. It is significantly an optimal algorithm for image text recognition.

关键词： canny edge detection algorithm k-means algorithm Image text recognition Noise removal

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Sub-Pixel edge detection algorithm Based on canny-Zernike Moment Method

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JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS 2020年第15期29卷

作者： Huang, Cheng Jin, Wei Xu, Qian Liu, Ziqi Xu, Zhiliang Nanjing Univ Sci & Technol Sch Automat Nanjing 210094 Peoples R China

In order to solve the problems of low efficiency and long running time caused by the traditional Zernike moment method for convolution calculation of the whole image, this paper combines the canny detection algorithm with the Zernike moment method. First, the canny edge detection algorithm, which combined with the Otsu threshold method, is used to extract the pixel edge of the image. Then an improved Hough transform method is used to fit the geometric edge in the image. Based on this, the Zernike moment method is applied to realize sub-pixel positioning of images. The algorithm improves the deficiencies of direct sub-pixel detection, improving accuracy and reducing running time. To verify the effectiveness of the proposed algorithm, the algorithm is applied to the dimension measurement experiment of T-type guide way. The results clearly show that the algorithm is superior to the traditional algorithm in accuracy.

关键词： Zernike moment sub-pixel canny edge detection algorithm Hough transform method

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Design of canny edge detection Hardware Accelerator Using xfOpenCV Library 3rd

Design of Canny Edge Detection Hardware Accelerator Using xf...

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International Conference on Computational Vision and Bio-Inspired Computing (ICCVBIC)

作者： Vashist, Lokender Kumar, Mukesh Natl Inst Technol Kurukshetra Kurukshetra 136119 Haryana India

ISBN: (纸本)9783030372187;9783030372170

Real time image processing using CPU takes more computational power and thereby processing speed also decreases. FPGA with its parallel processing capability does complex processes with much more speed and less power consumption sharing load of CPU hence it can be used for edge detection in real time where large number of pixels are to be processed. In this paper we developed programmable logic for canny edge detection algorithm intended for Zynq 7000 based Zybo board. xfOpenCV library is used to generate the hardware logic for algorithm after application of a wrapper function so as to make it portable with AXI stream interface of Zynq device. Better edges are detected even for noisy image using xfOpenCV library. Resources utilization of FPGA are very less thus the edge detection done using Zynq 7000 device will be 100x faster and more reliable then CPU's

关键词： xfOpenCV library Vivado HLS canny edge detection algorithm Zybo board

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Sizing of multiple cracks using magnetic flux leakage measurements

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IET SCIENCE MEASUREMENT & TECHNOLOGY 2010年第1期4卷 1-11页

作者： Ravan, M. Amineh, R. K. Koziel, S. Nikolova, N. K. Reilly, J. P. McMaster Univ Dept Elect & Comp Engn Hamilton ON Canada Reykjavik Univ Sch Sci & Engn Reykjavik Iceland

This study presents an approach to estimate the characteristics of multiple narrow-opening cracks from magnetic flux leakage (MFL) signals. The number, locations, orientations and lengths of the cracks are the objective of the inversion process. The proposed procedure provides a reliable estimation of crack parameters in two separate consecutive steps. In the first step, the canny edge detection algorithm is used to estimate the number, locations, orientations and lengths of the cracks. Then, an inversion procedure based on space mapping is used in order to estimate the crack depths efficiently. The accuracy of the proposed algorithm is examined via simulations based on the finite element method as well as real experimental MFL data.

关键词： magnetic leakage magnetic flux leakage measurements space mapping crack parameter estimation edge detection canny edge detection algorithm multiple crack sizing multiple narrow-opening cracks parameter estimation Fracture mechanics and hardness (mechanical engineering) Fracture mechanics, fatigue, and cracks cracks Numerical analysis finite element method magnetic flux crack depths finite element analysis Numerical approximation and analysis

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Estimation of soybean leaf area, edge, and defoliation using color image analysis

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2018年 150卷 41-51页

作者： Liang, Wei-zhen Kirk, Kendall R. Greene, Jeremy K. Clemson Univ Edisto Res & Educ Ctr Dept Plant & Environm Sci 64 Res Rd Blackville SC 29817 USA

Soybeans are an extremely important crop in the United States, providing the largest source of animal protein feed and a main source of vegetable oil in the country. The goal of this research is to identify methodologies to estimate percent defoliation of the soybean canopy and leaves using RGB images taken in the field. The Mahalanobis distance classification method was used to process sets of images and calculate leaf area (number of pixels) corresponding to two classes (leaf and background) with eight different color groups. The canny edge detection algorithm provided an efficient method for detecting leaf edges, and threshold t(2) = 20 was found to be the optimal value for estimating soybean leaf edge. The segmentation results showed a performance of 96% for soybean leaves using Mahalanobis distance classification. Two statistical regression models (polynomial and logistic regression) for defoliation of soybean were developed based on individual images of trifoliate leaves taken from the field. The models both utilized leaf area and edge to provide estimates of soybean defoliation;however, a logistic equation has potential to provide greater understanding and more accurate estimates of defoliation with variations, especially at low defoliation. The R-2 and root mean square error (RMSE) of estimated and observed defoliation of trifoliate leaves were 0.90 and 6.16%, respectively. The validation of soybean canopy defoliation and its corresponding trifoliate leaves defoliation also provided reasonable correlation (R-2 = 0.96 and RMSE = 1.85%). This approach could lead to use of remotely sensed imagery for estimating defoliation in soybeans and timely intervention with integrated pest management strategies.

关键词： Soybean Mahalanobis distance canny edge detection algorithm Defoliation Statistical regression

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Machine vision-based measurement approach for transverse vibrations of moving hoisting vertical ropes in mine hoists using edge location

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MEASUREMENT & CONTROL 2019年第5-6期52卷 554-566页

作者： Wu, Ganggang Xiao, Xingming Yao, Jiannan Song, Chunyang China Univ Min & Technol Sch Mechatron Engn Xuzhou 221116 Jiangsu Peoples R China Nantong Univ Sch Mech Engn Nantong Peoples R China

Hoisting vertical rope is a continuum of one-dimensional movement during operation of hoist, and there are no appropriate ways to measure its vibration displacement at present. In this paper, a non-contact and unmarked machine vision measurement method is proposed for measuring the transverse vibration displacement of hoisting vertical ropes. First, we construct the background image to extract the ropes by the background difference method. Subsequently, a novel row-column data statistics filtering algorithm is proposed and applied to the edge detection image for removing the edges of the unmeasured rope. Finally, Hough transformation is used to locate the two edge lines at the boundary of rope and obtain the line parameters, which can be used to calculate the vibration displacement of the measured points at different times. The transverse vibration displacement of a moving hoisting vertical rope in a mine hoist was measured by using the reported machine vision measurement method, verifying the feasibility of the method. In order to verify the validity of the method, a simulation experimental system was built. The proposed method and the laser displacement sensor were used to measure the artificial transverse vibration displacement of a vertical rope simultaneously. The two results are in good consistency, which indicates that the proposed method can be fairly reasonable and accurate to measure the transverse vibration displacement of vertical rope in mine hoists.

关键词： Machine vision canny edge detection algorithm Hough transformation row-column data statistics filtering vibration measurement hoisting vertical ropes

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Design and Implementation of Location algorithm for Rubber tapping robot 41

Design and Implementation of Location Algorithm for Rubber t...

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第41届中国控制会议

作者： Mingxiu Lin Bingge Yu Feng Pan Northeastern University College of Information Science and Engineering

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In recent years,new agricultural production methods and rapidly developing new technologies have promoted the development of agricultural equipment,giving birth to intelligent equipment and agricultural *** robots have great advantages in improving rubber *** at the problem of robot-based navigation and positioning and rubber tree incision recognition,a set of SLAM system based on lidar is designed,which is mounted on the robot to realize navigation and positioning,and uses the combination of monocular and binocular cameras to identify the incision and realize the position of the *** the design of system algorithms such as sensor data reading and motion control,the robot navigation adopts the optimized SLAM *** robot's position and direction are determined through the combination of the GPS positioning module and the IMU inertial navigation module,and the rubber tree positioning is realized through the A* *** incision recognition adopts the canny edge detection algorithm,color detection,artificial marking and other methods to realize the local positioning of the rubber tree rubber tapping *** comparative experiments were carried out in this *** to the analysis of the experimental results,it is verified that the system has achieved the expected goals,and has the characteristics of good accuracy and high real-time performance,which provides a reference for the research and application of robots in the field of rubber tapping.

关键词： navigation and positioning monocular camera canny edge detection algorithm color detection

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Advances in Vision based Lane detection algorithm Based on Reliable Lane Markings 5

Advances in Vision based Lane Detection Algorithm Based on R...

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5th International Conference on Advanced Computing and Communication Systems (ICACCS)

作者： Priyadharshini, P. Niketha, Pulugurtha SaanthaLakshmi, K. Sharmila, S. Divya, R. Sri Krishna Coll Technol Elect & Elect Engn Coimbatore Tamil Nadu India

ISBN: (纸本)9781538695333

This paper advances in a vision based driver assistance system for effective lane detection Technique. First method involves image processing technique initially to convert the Red, green and blue (RGB) into grayscale images takes place by removing the effects of shades and immersion data of the images by maintaining the brightness of the images. Then to remove the sound available in the images and the obtained video is allowed to pass through the Gaussian filter in-order to remove sound from the images. The edges recognition is an important function to identify and detect the sharp break in an image by canny edge detection algorithm. Then Hough transform technique is applied to obtain the image pixels in the form of long straight line in the Hough space. So we can detect the lane if the vehicle tends to deviate from the lane in a complex situation and take corrective measures to change the lane.

关键词： vision based driver assistance system Gaussian blur filter canny edge detection algorithm Hough Transforms

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Salvaging tumor from T1-weighted CE-MR images using automatic segmentation techniques

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International Journal of Information Technology (Singapore) 2022年第4期14卷 1869-1874页

作者： Saraswat, Amar Sharma, Neeta Department of CSE/ IT Noida International University Greater Noida India

When there exists a massive growth of abnormal cells inside the human brain, it is called as Brain Tumour. One of the major challenges in Content Based Image Retrieval (CBIR) is the semantic gap, which is extraction of the information between the human evaluator and Magnetic Resonance Imaging (MRI) machines. In the present scenario, the radiologist manually checks for the tumour region segmentation and outlines of that region. This problem can be reduced, if we combine the high-level and low-level feature extraction. In the proposed work, this gap is being bridged out, by using deep learning feature extraction technique over T1-weighted Contrast Enhanced-Magnetic Resonance (CE-MR) images along with canny edge, Gradient Descent Cost Minimization, Loss function evaluation and measurement of similarity through distribution vector and closed form metric learning as an automation segmentation technique to obtain the more precise accuracy. Also, the mean accuracy precision determined by the proposed model is 94.6% for the several query images sets. By this, manual efforts could be minimized in identifying the granular details of the tumours present in the several parts of the brain by employing MR images. © 2022, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.

关键词： canny edge detection algorithm Content Based Image Retrieval (CBIR) Contrast Enhanced-Magnetic Resonance (CE-MR) images Magnetic Resonance Imaging (MRI) Transfer Learning

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