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11th IEEE International Conference on Mechatronics and Automation (ICMA)

作者： Rong, Weibin Li, Zhanjing Zhang, Wei Sun, Lining Harbin Inst Technol State Key Lab Robot & Syst Harbin 150006 Heilongjiang Pr Peoples R China

ISBN: (纸本)9781479939794

The traditional canny edge detection algorithm is sensitive to noise, therefore, it's easy to lose weak edge information when filtering out the noise, and its fixed parameters show poor adaptability. In response to these problems, this paper proposed an improved algorithm based on canny algorithm. This algorithm introduced the concept of gravitational field intensity to replace image gradient, and obtained the gravitational field intensity operator. Two adaptive threshold selection methods based on the mean of image gradient magnitude and standard deviation were put forward for two kinds of typical images (one has less edge information, and the other has rich edge information) respectively. The improved canny algorithm is simple and easy to realize. Experimental results show that the algorithm can preserve more useful edge information and more robust to noise.

关键词： Edge detection canny algorithm Gravitational field intensity operator Adaptive threshold

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An improved dynamic double threshold canny edge detection algorithm 11

An improved dynamic double threshold Canny edge detection al...

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11th International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR) - Pattern Recognition and Computer Vision

作者： Xiao, Zhikang Zou, Yang Wang, Zhen Wuhan Inst Technol Sch Elect & Informat Engn Wuhan 430205 Peoples R China

ISBN: (纸本)9781510636385

With the upgrade of the industry, robots urgently need to track moving targets at high speed. Therefore, the detection algorithms in machine vision technology need to be improved. Aiming at the problem that high and low thresholds need to be fixed in traditional canny edge detection algorithm, an improved dynamic double threshold canny algorithm is proposed. Constantly increasing the size of the threshold, Using the size of the area where the image edge is closed as a standard, finally to determine the best threshold, In order to achieve the best detection effect. Experimental results show that, Improved dynamic double threshold canny algorithm not only improves the edge detection effect by 9% on average compared with the traditional algorithm, but also detects more complete image information and has stronger adaptability.

关键词： edge detection closed area dynamic threshold canny algorithm adaptability

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An Efficient Design for canny Edge Detection algorithm using Xilinx System Generator 3

An Efficient Design for Canny Edge Detection Algorithm using...

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3rd IEEE International Conference on Research in Intelligent and Computing in Engineering (RICE)

作者： Mahalle, Avinash G. Shah, A. M. Govt Coll Engn Dept Elect Engn Amravati Maharashtra India

ISBN: (纸本)9781538625996

Digital Image consists of some informative pixels and some redundant pixels. Edge Detection is the process of preserving informative pixels and eliminating redundant data which improves bandwidth and storage efficiency. A sudden change in pixel intensity level is defined as an Edge. Theoretically, from the literature it is seen that canny edge detection is the most accurate algorithm. It is also insensitive to Noise. The only disadvantage of canny algorithm is its high computational complexity which limits its maximum frequency of application with high latency and low throughput. In this paper, tradeoff between Accuracy and Complexity is studied. An efficient canny algorithm is designed using Xilinx System Generator which utilizes JTAG Hardware co-simulation approach. An accuracy is compromised in order to make it more efficient in terms of resource utilization than the conventional one. Spartan-3E FPGA is used as a reconfigurable hardware platform for the designed algorithm.

关键词： Image Processing Edge Detection canny algorithm Xilinx System Generator Spartan-3E FPGA

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IMAGE IDENTIFICATION OF A MOVING OBJECT BASED ON AN IMPROVED canny EDGE DETECTION algorithm

IMAGE IDENTIFICATION OF A MOVING OBJECT BASED ON AN IMPROVED...

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ASMEInternational Mechanical Engineering Congress and Exposition (IMECE2018)

作者： Liu, Yang Sun, Lingyu Li, Lijun Zhang, Yiben Dai, Zongmiao Xiong, Zhenkai Beihang Univ Sch Transportat Sci & Engn Beijing 100191 Peoples R China Zhengzhou Electromech Engn Res Inst Zhengzhou 40015 Henan Peoples R China

ISBN: (纸本)9780791852033

Edge detection plays an increasingly critical role in image process community, especially for moving object identification problems. For this case, the target object can be captured straightly via the edges beside which there is an obvious jump of grey value or texture. Nowadays, canny operator has gained great popularity as it shows higher anti-noise performance and presents better detection accuracy in comparison with other edge detection operators like Robert's, Sobel's, Prewitt's etc. However, the Gaussian filter associated with the classic canny operator is sometimes too simple to decrease the all-type-noise. Additionally, in order to enhance the detection accuracy and lower the pseudo-edges detection ratio, two thresholds, high and low, are chosen artificially which have actually limited the adaptability of the algorithm. In this work, a compound filter, Gaussian-Median filter, is proposed to improve the smoothing effect. The self-adaptive multi-threshold Otsu algorithm is realized to determine the high/low threshold automatically according to the grey value statistic. Image moment method is conducted on basis of the detected moving object edges to locate the centroid and to compute the principal orientation. The experimental results based upon locating the edges of both static and moving objects proved the good robustness and the excellent accuracy of the proposed method.

关键词： Edge detection canny algorithm Multi-threshold Otsu method Moving object Image moment.

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Multi-scale Harris Corner Detection algorithm Based on canny Edge-Detection

Multi-scale Harris Corner Detection Algorithm Based on Canny...

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IEEE International Conference on Computer and Communication Engineering Technology (CCET)

作者： Shi Guiming Suo Jidong Dalian Maritime Univ Informat Sci & Technol Coll Dalian Peoples R China Dalian Univ Sci & Technol Sch Elect Engn Dalian Peoples R China

ISBN: (纸本)9781538674376

Harris algorithm is a classical corner detection algorithm, it has affine invariant and partial rotational invariance. But it does not have the scale invariance, and it has poor real-time and adaptability. This paper will put forward a new corner detection algorithm which based on improved canny edge detection algorithm and improved multi-scale Harris corner detection algorithm. First the edge information of the target can be got by the improved canny algorithm. Then process the original image by the Mean-Shift filter. At last adopts improved multi-scale Harris algorithm to detect the corners from the edge information, and marks the position of the corners in the original image. According to the experimental results, the new method shows that the corners distribute equably and have high accuracy. At the same time combine scale invariance and rotational invariance. The new method greatly improves image corner detection performance compared with the traditional Harris algorithm.

关键词： corner detection canny algorithm harris algorithm mean-shift filter

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Application and improvement of canny edge-detection algorithm for exterior wall hollowing detection using infrared thermal images

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ENERGY AND BUILDINGS 2022年 274卷

作者： Lu, Youcun Duanmu, Lin Zhai, Zhiqiang (John) Wang, Zongshan Dalian Univ Technol Fac Infrastruct Engn Dalian 116024 Peoples R China Univ Colorado Dept Civil Environm & Architectural Engn Boulder CO 80309 USA

The periodic hollowing inspection of the existing building exterior wall is crucial for public safety and building energy conservation. Due to its non-destructive and intuition advantage, the infrared thermal detection is proposed to be an ideal survey method. However, much manual participation is required to distinguish the hollowing flaw relying on empirical judgment, and a heavy burden comes up when large-area diagnosis required. In order to improve the efficiency of hollowing detection, this investigation developed the canny algorithm to realize the automatic processing using the computer instead of manual judgment. At first, reasonable pieces of setting advice were given to get more clear hollowing region contours with the final recognition outcome comparison of different processing methods for each step. Besides, it was found that the hollowing contour gradient values are lower and exist in a short interval, and the segmen-tation threshold value was critical in the canny edge-detection algorithm, which highly restricted the speed of processing large amounts of infrared images. To improve the efficiency of thermal image recog-nition, a threshold selection method based on the local maximum inter-class variance algorithm was introduced into the canny edge-detection algorithm. Compared with Sobel, Roberts, Prewitt, and LoG, the proposed algorithm presented a better performance in the identification of hollowing edge contour according to the verification based on three cases. It revealed that the improved canny edge-detection algorithm was effective and efficient, which could not only eliminate the influence of subjective factors but also achieve full-automatic and batch processing. (c) 2022 Elsevier B.V. All rights reserved.

关键词： Wall hollowing Infrared thermal imaging Thermal defect distinguish Temperature detection canny algorithm Threshold selection

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Research on Improving canny Edge Detection algorithm in the Binocular Visual Recognition for Hazardous Chemical Warehouse

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电脑学刊 2020年第3期31卷 337-350页

作者： Yong-Yan Hong-chao Ma Ze-Chen Huang Kai-Li Li Bo-Tao Wang Yang-Li Jian-Shi

The safety distance monitoring in the hazardous chemical warehouse is the key to ensure the safe storage of hazardous chemicals. Binocular vision is one of the promising technical means. The canny edge detection algorithm in the binocular vision of the warehouse is an effective algorithm for the boundary extraction of the dangerous goods used in warehouse, but the algorithm faces the salt and pepper noise interference in the warehouse where has a complex environment. Firstly, adaptive median filtering is used to denoising. Then iterative mean method and Otsu method is used to adaptively set threshold and extract edges. Under normal lighting, night vision, night vision and light interference, carry on experimental research on storage stacks such as warehouse model boxes and cylinders. The results show that the improved algorithm significantly improves denoising effect and edge extraction accuracy.

关键词： canny algorithm hazardous chemicals storage iterative mean median filtering Otsu

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The Multi-Scale Hough Transform Lane Detection Method Based on the algorithm of Otsu and canny

The Multi-Scale Hough Transform Lane Detection Method Based ...

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2014 3rd International Conference on Key Engineering Materials and Computer Science(KEMCS 2014)

作者： Yu Chai Sujing Wei Xinchun Li Xi'an University of Science and Technology

In order to improve the accuracy of detecting lane for automatic vehicle driving, a method for detecting the straight part of Lane is proposed, which is the Multi-Scale Hough transform method for lane detection based on the algorithm of Otsu and canny. First of all, by the methods of Otsu to segment image and use the morphology operation of erode and dilate to wipe off the information of roadside trees and fences to strengthen the road boundary *** the lane edge and feature is gained by the canny operator. At last, using Standard Hough Transform, Progressiveness Probabilities Hough Transform and Multi-Scale Hough Transform complete the detection of lane's straight part. The experimental results show that, Multi-Scale Hough Transform method can accurately detect the lane line and provide the reliable basis for the path planning, automatic follow-up vehicle driving and lane departure warning.

关键词： Otsu algorithm canny algorithm Lane detection Multi-Scale Hough Transform

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An Improved canny Edge Detection algorithm

An Improved Canny Edge Detection Algorithm

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2017 IEEE 8th International Conference on Software Engineering and Service Science

作者： Li Xuan Zhang Hong School of Electronic Information Engineering Shenyang Aerospace University

The traditional canny algorithm has been applied to image edge detection. However, this traditional algorithm can’t adaptively determine the filtering threshold value and it can’t separate targets from background, when filtering the lower contrast image. Therefore, in response to these problems, this paper proposed an improved method on canny algorithm. Two adaptive thresholds were obtained by doing differential operation on amplitude gradient histogram. Then we connected edge points to get some generalized chains. After that, it needed to calculate their mean value to delete generalized chains, which are smaller than the mean value. Finally, the image edge detection results were got by linear fitting method. Experimental results show that the improved algorithm is more robust to noise and it can clearly separate targets from background.

关键词： edge detection canny algorithm adaptive threshold generalized chains linear fitting method

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canny Edge Detection algorithm Based on Improved Sequential Statistical Filter

Canny Edge Detection Algorithm Based on Improved Sequential ...

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第三十九届中国控制会议

作者： Liu Zhi-ying Xie Chun-is Li Jin-jun Sang Yu Wu Shuai Midshipmen Group Five Dalian Naval Academy Dept.of Missile Dalian Naval Academy

This paper describes an improved canny edge detection algorithm to detect edge of infrared image better through overcoming the complexity and intensity of infrared image noise acquired by missile-borne radar seeker. Based on the traditional canny algorithm architecture, the improved Sequential Statistical Filtering（ISSF） algorithm is used to replace Gauss filtering algorithm, and the P-entropy method（PEM） and OTSU threshold（PEM and OTSU, POM） are used to self-adaptively select the two thresholds for edge extraction. Experiments show that the algorithm can eliminate noise interference better and has higher edge detection effect for infrared images.

关键词： canny algorithm Improved sequential statistical filtering P-entropy method OTSU threshold Self-adaption

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