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Scratch Detection algorithm of Car Surface Based on Directional Color susan Operator

Transactions of Nanjing University of Aeronautics and Astronautics 2019年第3期36卷 479-487页

作者： WANG Zhen XIE Qiang DING Qiulin College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics

The car surface scratch detection adopts the traditional manual detection with poor efficiency and high missing *** of the gray mark and the background of car surface scratches,the traditional edge detection algorithm cannot meet the needs of car surface scratch ***,the directional susan algorithm based on CIELab color space is adopted in this *** direction template and the circle template to calculate the color difference of the color image are used in the algorithm which has been converted to the CIELab *** edges and scratches are eliminated by matching and contrasting the detected image with the edge *** results show that the algorithm can effectively detect scratches on the surface of cars,improve the detection speed and reduce the undetected rate.

关键词： scratch detection directional template CIELab space susan algorithm

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Analysis and improvement of susan algorithm

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SIGNAL PROCESSING 2012年第10期92卷 2552-2559页

作者： Gao, Chao Zhu, Hongjun Guo, Yongcai Chongqing Univ Minist China Key Lab Optoelect Technol & Syst Educ Chongqing 400030 Peoples R China

A modified Smallest Univalue Segment Assimilating Nucleus (susan) algorithm based on the local gray value character of an image is presented here. Beginning with an explanation of the principle of edge detection and noise reduction, we find susan algorithm is immune to all noise points but the isolated noise points. To improve this, an original edge response formulation is optimized by imposing constraint conditions. Then a set of anti-noise tests were run to compare our scheme with the original algorithm and other popular edge detectors. The results show that for Gaussian noise and salt-and-pepper noise, the improved susan algorithm performs much better than the original one in view of sensitivity to noise and detection of edges, and especially for salt-and-pepper noise the improved susan algorithm works best among the all detectors tested here. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Edge detection susan algorithm Noise cancellation

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Research on auto-focusing technology for micro vision system

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OPTIK 2017年 142卷 226-233页

作者： Sha, Xiaopeng Li, Wenchao Lv, Xiaoyong Lv, Jiangtao Li, Zhiquan Northeastern Univ Qinhuangdao Sch Control Engn Qinhuangdao 066004 Peoples R China Yanshan Univ Inst Elect Engn Qinhuangdao 066004 Peoples R China

The paper presents a passive auto-focusing technology by combining the discrete cosine transform(DCT) algorithm and small univalve segment assimilating nucleus(susan) algorithm with evaluation function. The new method has the advantage of unimodal, local extremum and sensitivity of the focus curve. For the focusing search algorithm, the improved mountain climbing method which combined the large step and small step has been proposed, it makes the micro-vision system could find the focal plane more quickly and accurately. (C) 2017 Elsevier GmbH. All rights reserved.

关键词： Auto-focusing DCT susan algorithm Climbing algorithm

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Novel Image Segmentation algorithm Based on Automatic GVF Snake Model

Novel Image Segmentation Algorithm Based on Automatic GVF Sn...

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2018 International Conference on Modeling, Simulation and Optimization(MSO 2018)

作者： Xue-gang HU Xiu-lan QIU Hong-jing TANG College of Communication and Information Engineering Chongqing University of Posts and Telecommunications Research Center of System Theory and its Applications Chongqing University of Posts and Telecommunications

To address issues that GVF Snake model needs to initialize the contour manually so that image segmentation cannot be automatically handled,the effect of segmentation is also related to the initial contour,and its efficiency and accuracy of the model are not ideal,a novel algorithm for image segmentation based on automatic GVF Snake model is proposed in this *** introduce the concepts of "flat redundant point" and " fitting outsourcing polygon".In our algorithm the discrete feature edge points set of target image is first obtained by susan corner detection ***,finding the fitting outsourcing polygon of discrete edge points set,Finally,the GVF Snake curve is evolved by using the fitting outsourcing polygon as the initial contour curve to complete the image *** is not only proved that the fitting outsourcing polygon as the initial contour curve can converge to the real target image edge by the algorithm in theory,but the experimental results also show that the proposed algorithm can effectively improve the segmentation accuracy,greatly reduce the number of iterations of the model,and improve the efficiency of the algorithm.

关键词： Image segmentation Gradient vector field Snake model susan algorithm Initial contour Fitting outsourcing polygon

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SAR image registration based on susan algorithm

SAR image registration based on Susan algorithm

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International Symposium on Lidar and Radar Mapping - Technologies and Applications

作者： Wang, Chun-bo Fu, Shao-hua Wei, Zhong-yi Liaoning Prov Commun Coll Shenyang 110122 Liaoning Peoples R China Shenyang Surveying & Mapping Inst Shenyang 110015 Liaoning Peoples R China Shenyang Agr Univ Shenyang 110866 Liaoning Peoples R China

ISBN: (纸本)9780819489333

Synthetic Aperture Radar (SAR) is an active remote sensing system which can be installed on aircraft, satellite and other carriers with the advantages of all day and night and all-weather ability. It is the important problem that how to deal with SAR and extract information reasonably and efficiently. Particularly SAR image geometric correction is the bottleneck to impede the application of SAR. In this paper we introduces image registration and the susan algorithm knowledge firstly, then introduces the process of SAR image registration based on susan algorithm and finally presents experimental results of SAR image registration. The Experiment shows that this method is effective and applicable, no matter from calculating the time or from the calculation accuracy.

关键词： Synthetic Aperture Radar image registration susan algorithm character extraction

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Moving shadow detection based on susan algorithm

Moving shadow detection based on Susan algorithm

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2011 IEEE International Conference on Computer Science and Automation Engineering(CSAE 2011)

作者： Huang Si-ming Liu Bing-han College of Mathematics and Computer Science FuZhou University Fuzhou China Wang Wei-zhi College of Civil Engineering FuZhou University Fuzhou China

In Intelligent Transportation Systems moving shadows have always been wrongly detected as foreground objects, thus causing bad effect on the latter targets tracking and identify. In order to subtract the shadows lie in different circumstances,there has put forward a method of moving shadow detection based on Image edge detection which using susan algorithm[9]. After getting the background with mixture Gaussian distribution the moving foreground position can be accurately obtained via the background subtraction method, then use the susan algorithm to detect the image edge in interested area. Finally do shodow detection by analyzing the statistic characteristics of edge pixels. According to the experiment, this method is easy to operate and possesses high rate of accuracy, low rate of complexity, and well adapt to different kinds of shoadow distribution.

关键词： Gaussian distribution foreground area susan algorithm edge shadow segmentation

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Deep Space Moving Target Detection Based on Technology of Image Matching

Deep Space Moving Target Detection Based on Technology of Im...

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26th Chinese Control and Decision Conference (CCDC)

作者： Xiu Ha-ning Zhu Sheng-ying Cui Ping-yuan Beijing Inst Technol Sch Aerosp Engn Beijing 100081 Peoples R China

ISBN: (纸本)9781479937066

A detection method of moving targets in deep space is researched based on technology of image registration. According to the characteristics of deep space image information, a susan feature point extraction algorithm is modified to inhibit isolated noises which are similar to sidereal feature points, and it effectively eliminates isolated noises. The geometric constraint among stars in the star image settles a feature points matching algorithm. Finally, matching of two images by affine transformation and differential option locates the moving target. Trials show that this method realizes moving targets detect and search in deep space where detector is under the condition with various disturbances.

关键词： Feature point extraction susan algorithm Feature points matching Image matching Differential option

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Image Registration of CT and DR Based on Improved susan

Image Registration of CT and DR Based on Improved SUSAN

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7th International Conference on MEMS, NANO and Smart Systems (ICMENS 2011)

作者： Han Ping Xu Bai-Sen Wuhan Univ Technol Wuhan 430070 Peoples R China Henan Univ Technol Zhengzhou Peoples R China

ISBN: (纸本)9783037853122

The paper completes image registration of medical CT and DR through improved susan algorithm. First, the paper divides the image into a certain number of anatomical point regions with some significance, and sets different grayscale D-value for different regions to make corners distribute equably. Second, the paper uses the size of the USAN from limited corner regions to reduce the number of corners and the computation. Then the paper adopts confidence algorithm, find the correct match points by setting threshold, and thus completes image registration.

关键词： image registration Confidence degree susan algorithm

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An improved susan algorithm for the electronic image stabilization of the UAV video image

An improved SUSAN algorithm for the electronic image stabili...

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Conference on Electronic Imaging and Multimedia Technology V

作者： Zhao Hongying Cheng Yinqian Li Guo Peking Univ Inst Remote Sensing & Geog Informat Syst Beijing Key Lab Spatial Inf Integrat & Its Applic Beijing 100871 Peoples R China China Univ Min & Technol Coll Mech Elect & Informat Engn Beijing 100083 Peoples R China

ISBN: (纸本)9780819470089

A new image corner detection algorithm is proposed in this paper based on the susan algorithm for the electronic image stabilization of the UAV video image, Through analyzing the gray characteristics of the image of the UAV, the new algorithm changed the judge criteria of the susan corner detection algorithm to increase the accuracy and velocity of the image processing. The basic steps of the algorithmic show as follow: First, the correct threshold is decided using the gray characteristic. Second, comparing the one pixel with the eight neighborhood pixels, the elementary direction of corner is acquired. Last, a corner is acquired through calculating the number of the congener pixels based on these new directions. Using this new algorithm the corners should be detected fast and efficiently. Experimental results of the UAV video image processing show that the new method can highly increase computational velocity. Consequently the proposed algorithm meets the need for real-time image processing,

关键词： UAV susan algorithm gray electronic image stabilization corner detector

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Online detection of beer bottle based on optical flow field segmentation and susan algorithm

Online detection of beer bottle based on optical flow field ...

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1st International Congress on Image and Signal Processing

作者： Zhang, Daode Zhang, Yepeng Kang, Zhiqiang Huazhong Univ Sci & Technol Sch Mech Engn Wuhan 430074 Peoples R China Hubei Univ Technol Sch Mech Engn Wuhan 430068 Peoples R China

ISBN: (纸本)9780769531199

To realize fast defect detection on moving object, a fusion algorithm based on segmentation of optical flow field and susan's operator a method was put forward under the condition of camera being fixed. The method first finishes the area segmentation depending upon the image segmentation algorithm of optical flow field, then takes advantage of edge detection precision of susan operator to get the detailed edge map of object area. The experiments based on the fusion algorithm have shown encouraging results of fast detecting the surface defect of cylindrical moving object on product line.

关键词： computer vision optical flow field moving object surface defect susan algorithm

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