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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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A Fast Detection algorithm of harris Apparent Corners Based on the Local Features

A Fast Detection Algorithm of Harris Apparent Corners Based ...

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9th World Congress on Intelligent Control and Automation (WCICA)

作者： Zhang, Huanghui Xu, De Chinese Acad Sci Inst Automat Key Lab Complex Syst & Intelligence Sci Beijing Peoples R China Chinese Acad Sci Grad Univ Beijing Peoples R China

ISBN: (纸本)9781612847009

A fast apparent corner detection algorithm based on the local features is proposed in this paper. Firstly, the pixels on each side of the grid region are stretched out, and the edge points of the object on each side are detected according to the differences of the gray values of the pixels. The number of the edge points is employed to decide whether the grid contains a corner or not. Then the candidate grids that do not contain a corner are removed via checking the angle between the edges of the object. The method of average position is used to exclude gathered corners. Then the remained corners are taken as candidate corners. Finally, the harris algorithm is applied to the small area around each candidate corner to get the apparent corners. Experimental results verify the effectiveness of the proposed algorithm.

关键词： corner detection harris algorithm apparent corner

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Multilevel Wavelet Decomposition Based harris Corner Detection algorithm for Remote-sensing Image

Multilevel Wavelet Decomposition Based Harris Corner Detecti...

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2018 3rd International Conference on Computational Modeling, Simulation and Applied Mathematics (CMSAM 2018)

作者： Bing ZHOU Xiao-xing NIU Xiao-nan LIU Xin-xin YANG Henan University

Because of the interference of the noise and the subtle texture, the harris algorithm will generate much more false corners. An improved harris algorithm based on multilevel wavelet decomposition is proposed. By multilevel wavelet decomposition, the high frequency components of image are extracted. These high frequency components with different scales are parsed, and the noises and subtle textures are suppressed while the original image edge features are kept. The final experiment shows that the improved corner detection algorithm can effectively reduce the number of false corners.

关键词： Remote-sensing image Multilevel wavelet decomposition Corner detection harris algorithm

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harris corner detection on a NUMA manycore

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2018年 88卷 442-452页

作者： Haggui, Olfa Tadonki, Claude Lacassagne, Lionel Sayadi, Fatma Ouni, Bouraoui Sousse Natl Sch Engn Networked Objects Control Commun Syst Lab NOCCS Sousse Tunisia PSL Res Univ Mines ParisTech CRI Paris France Sorbonne Univ CNRS LIP6 Paris France Univ Monastir FSM Fac Sci Elect & Microelect Lab Monastir Tunisia CRI Paris France

Corner detection is a key kernel for many image processing procedures including pattern recognition and motion detection. The latter, for instance, mainly relies on the corner points for which spatial analyses are performed, typically on (probably live) videos or temporal flows of images. Thus, highly efficient corner detection is essential to meet the real-time requirement of associated applications. In this paper, we consider the corner detection algorithm proposed by harris, whose the main work-flow is a composition of basic operators represented by their approximations using 3 x 3 matrices. The corresponding data access patterns follow a stencil model, which is known to require careful memory organization and management. Cache misses and other additional hindering factors with NUMA architectures need to be skillfully addressed in order to reach an efficient scalable implementation. In addition, with an increasingly wide vector registers, an efficient SIMD version should be designed and explicitly implemented. In this paper, we study a direct and explicit implementation of common and novel optimization strategies, and provide a NUMA-aware parallelization. Experimental results on a dual-socket INTEL Broadwell-E/EP show a noticeably good scalability performance. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Corner detection harris algorithm Multicore Multithread SIMD GFLOPS NUMA Scalability

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Log-log scaled harris corner detector

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ELECTRONICS LETTERS 2010年第24期46卷 1602-1603页

作者： Ryu, J. -B. Park, H. -H. Chung Ang Univ Sch Elect & Elect Engn Seoul 156756 South Korea

The well-known harris algorithm for corner detection in digital images suffers from poor localisation especially in high (>= 3) order corners. In this reported work, the harris algorithm is extended to have better ... 详细信息

关键词： harris algorithm digital images gradient methods gradient vectors high order corners image pixels image recognition localisation performance log-log scaled harris corner detector

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Image registration based on mutual information and harris corner points

Image registration based on mutual information and Harris co...

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2nd International Conference on Advanced Design and Manufacturing Engineering (ADME 2012)

作者： Cheng, You-e Zhejiang Ind & Trade Polytech Collage Informat & Commun Wenzhou 325003 Zhejiang Peoples R China

ISBN: (纸本)9783037855034

A maximization of mutual information based image registration method is described. Firstly Due to the inferiority of image registration using maximum mutual information, the registration based on harris algorithm to obtain corner points. Secondly, the one to one matching points could be obtained through mutual information rough match Finally, the search strategy used the improved genetic algorithm to find the optimum value. Experimental results indicate the proposed algorithm can achieve better accuracy and good robust.

关键词： Image Registration Mutual Information harris algorithm Optimum Value

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harris Corner Detection based Leaf Image Segmentation for Ancient Chinese Books 10

Harris Corner Detection based Leaf Image Segmentation for An...

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10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Zhang, Jingjing Cai, Yuan Jiang, Wei Wang, Chuanyu Commun Univ China Fac Sci & Technol Beijing Peoples R China Minist Culture Key Lab Acoust Visual Technol & Intelligent Contr Beijing Peoples R China Beijing Key Lab Modern Entertainment Technol Beijing Peoples R China

ISBN: (纸本)9781538619377

In the image digitization process of ancient Chinese books, sometimes it is needed to extract the leaf from the original image and separate the left half and the right half. This paper proposes a leaf segmentation method based on harris corner detection to solve this problem. Firstly, the original image is preprocessed to recognize the contour information, and the minimum bounding rectangle is determined by the contour. Then, harris corner detection is used. In order to recognize the edge of the leaf, we traverse the corner points in the special area and save those points which meet the threshold requirement. At last, the edges of left half leaf and right half leaf are determined, and the segmentation is completed. The experimental results show that the proposed method achieves good performance in a class of leaf image segmentation.

关键词： corner detection harris algorithm leaf image segmentation

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An Improved harris Corner Points Detection for Low-Light Scenes Based on Contrast Limited Adaptive Histogram Equalization 6

An Improved Harris Corner Points Detection for Low-Light Sce...

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6th International Conference on Imaging, Signal Processing and Communications (ICISPC)

作者： Guo, Jiawei Ma, Jieming Garcia-Fernandez, Angel F. Ge, Ji Zhang, Yungang Xian Jiaotong Liverpool Univ XJTLU Sch Adv Technol Suzhou Peoples R China Univ Liverpool Liverpool Merseyside England Univ Nebrija ARIES Madrid Spain JITRI Micro Nano Automat Inst Suzhou Peoples R China Yunnan Normal Univ Kunming Yunnan Peoples R China

ISBN: (纸本)9781665454803

Corner points are commonly defined as the intersection of two edges, and the harris algorithm, which performs corner point detection based on the grey value variation between a patch and its neighborhood, is commonly used in various computer vision tasks. For low-light images, harris algorithm is affected because the details of the image become blurred by low contrast. This paper proposes an improved harris algorithm, which is inspired by the Contrast Limited Adaptive Histogram Equalization (CLAHE). After extracting a patch of the target image, the gray value of the patch is adjusted based on the cumulative distribution function (CDF). As a result, the gray value of the patch becomes evenly distributed, and the variation of the gray value of the patch becomes sharper. The improved harris algorithm has been compared with the original harris algorithm on different images of low-light scenes. Experimental results show that the proposed algorithm can effectively detect corner points in low contrast regions, and the repeatability of corner points matching in the low-light regions is significantly improved.

关键词： harris algorithm contrast limited adaptive histogram equalization corner points detection low light

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Circular Mask and harris Corner Detection on Rotated Images

Circular Mask and Harris Corner Detection on Rotated Images

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International Conference on Life System Modeling and Simulation (LSMS) / International Conference on Intelligent Computing for Sustainable Energy and Environment (ICSEE)

作者： Wang, Le Fei, Minrui Yang, Taicheng Shanghai Univ Sch Mechatron Engn & Automat Shanghai Key Lab Power Stn Automat Technol Shanghai 200072 Peoples R China

ISBN: (纸本)9789811063701;9789811063695

Corners are the key feature of image. Stable corners are particularly important in the industrial pipelining of beer cap surface defects detection, greatly affecting the efficiency of image matching and detection precision. To find a stable algorithm for the cap surface defects detection, Stable Corner and Stable Ration are proposed to evaluate the stability of corner detectors, which are able to give an intuitive and unified stability description of various corner detection algorithm. After comparing the stability with Difference of Gaussian (DOG) and Features from Accelerated Segment Test (FAST), harris is selected as the detector of cap surface images due to its high stability. To eliminate the redundant corners detected by harris, Circular Mask and harris (CMH) corner detection is proposed. In CMH, a circular mask with an adaptive threshold is adopted to remove the redundant corners, whereby comparing the intensity between the center pixel and others on the mask in a rapid way, more stable corners are obtained eventually. The effectiveness and robustness of CMH are verified in this paper, and the Stable Ratio increased by 16.7% relatively.

关键词： Image processing Corner detection harris algorithm Rotated image Stability Ratio

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A triangle mesh-based corner detection algorithm for catadioptric images

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IMAGING SCIENCE JOURNAL 2018年第4期66卷 220-230页

作者： Tran Dang Khoa Phan Univ Sci & Technol Univ Danang Dept Elect & Telecommun Engn Danang Vietnam

As with conventional images corner detection is an important aspect of many computer vision problems involving catadioptric images. However, classical image processing algorithms are no longer appropriate for catadioptric images due to nonuniform resolution and distortions of catadioptric images. In this paper, we propose a novel approach to corner detection for catadioptric images based on triangle mesh. First, we transform catadioptric images to spherical images by combining an improved projection model for central catadioptric cameras with triangle mesh for a unit sphere. Spherical images yield a spatially uniform resolution domain for processing catadioptric images. Then, based on the topology of a triangle mesh, variations of light intensity with respect to directions for each image patch are measured to detect corners. The proposed algorithm addresses problems of catadioptric image processing caused by non-uniform resolution and distortions of these images. Experimental results showed that comparing to widely used methods, the triangle mesh-based corner detection algorithm can achieve higher repeatability rate relative to different imaging condition changes.

关键词： Catadioptric image corner detection triangle mesh harris algorithm non-uniform resolution

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