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10th IEEE International Conference on Software Engineering and Service Science (ICSESS)

作者： Fan, WenTao Qiu, Kaijin Southwest Univ Coll Comp & Informat Sci Chongqing Peoples R China

ISBN: (纸本)9781728109459

The malfunctions detection of the high voltage electric wire mainly obtains the detection target image periodically by the drone and sends it back to the ground to compare the images to determine whether there is a failure. However, since the drone acquires images at different times in the sky, each time the image obtained is tilted, there is a certain difference in contrast and exposure, which seriously interferes with the detection of the fault. At present, image-based malfunction detection methods mainly include: methods based on image grayscale, shape and texture features, wavelet transform and image segmentation. These methods are complicated to operate and have long running time, which is difficult to meet the experimental requirements. We can detect the malfunctions by the distribution of the matching points of the image. The algorithm based on probability and statistics can reduce the effects of rotation, translation and noise during image processing. Dividing the image into blocks and calculating the number of image feature points to determine if there is a fault is simple and effective. Experimental results show that the algorithm can effectively detect whether the specified area is faulty.

关键词： image malfunction detection surf algorithm watershed algorithm image feature point

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An improved adaptive threshold BRISK feature matching algorithm based on surf

An improved adaptive threshold BRISK feature matching algori...

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Chinese Automation Congress (CAC)

作者： Li, Zifan Chen, Chen Wuhan Univ Technol Automat Sch Wuhan Hubei Peoples R China

ISBN: (纸本)9781728113128

This paper proposes an adaptive threshold image matching strategy based on the surf algorithm and the improved BRISK algorithm. The process of algorithm can be divided into four parts. First, histogram equalization is applied to enhanced the image. Then the surf threshold is determined by calculating the complexity of the image. After that, the surf detection is used to obtain the image feature points. Then the feature points are processed by BRISK descriptor. Finally, the Lowe's algorithm is adopted to obtain necessary matching points. The results of experiment verified that, compared with surf algorithm in speed, the improved algorithm has computational advantages, and the matching accuracy is obviously enhanced compared to the BRISK algorithm.

关键词： adaptive threshold the it information entropy histogram equalization BRISK algorithm surf algorithm

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An Image Retrieval algorithm Based on surf for Embedded System 10

An Image Retrieval Algorithm Based on SURF for Embedded Syst...

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10th International Conference on Intelligent Computation Technology and Automation (ICICTA)

作者： Yu Hai-yan Huang Yu-xin Zhengzhou Univ Sci & Technol Coll Informat Engn Zhengzhou 450064 Henan Peoples R China

ISBN: (纸本)9781538612309

To study the problem of real-time and accuracy of the image retrieval algorithm of embedded system with scale, rotation and illumination. Improved surf algorithm, which is applied to the binary image feature extraction, improve the real-time performance of the image, the use of LSH algorithm to establish the index of the image feature database, to avoid duplicate feature extraction, the use of LSH algorithm to approximate the search image features, and the similarity into line sort, select the best matching image. When the image has scale, rotation, illumination, this algorithm has a higher retrieval accuracy than the surf algorithm and ORB algorithm, and has a better robustness than the surf algorithm. The experiments show that the algorithm has scale, rotation and illumination conditions of the embedded system of image retrieval, has good real-time performance and achieved good application effect.

关键词： surf algorithm Embedded system image LSH algorithm image retrieval algorithm

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Research on surf Feature Matching algorithm Based on Lab Color Space 3

Research on SURF Feature Matching Algorithm Based on Lab Col...

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3rd International Conference on Robotics, Control and Automation Engineering (RCAE)

作者： Han, Leng Sun, Xia Wang, Jiawei Xia, Dingmei Chongqing Univ Posts & Telecommun Sch Adv Manufacture Chongqing Peoples R China Chongqing Inst Engn Elect Informat Sch Chongqing Peoples R China

ISBN: (纸本)9781728186382

The alignment of images is an important task in the processing of images, which is also known as registration. Among the feature based registration methods, Speeded Up Robust Features (surf) has been proposed as a computationally efficient approach. The surf algorithm not only does not consider color information, but the matching accuracy is also rather low. In this paper, an improved surf algorithm for feature extraction is proposed. An approach is proposed to use the Lab color space to extract the color information of the color image when extracting the feature points based on surf, and adds the feature descriptors. In this sense, the feature descriptors of different feature points by proposing method are unique. And this method makes up for the shortcoming that surf cannot use the color information of color images. This improved method promotes the precision of matching. The results show that the matching accuracy of this algorithm is higher than that of the original surf when physical interference, rotation, brightness change, and scale change occur.

关键词： surf algorithm color space image matching feature descriptor

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A fast image stitching algorithm based on improved surf 10

A fast image stitching algorithm based on improved SURF

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10th International Conference on Computational Intelligence and Security CIS 2014

作者： Zhu Lin Wang Ying Zhao Bo Zhang Xiaozheng China North Vehicle Res Inst Dept Informat & Control Beijing Peoples R China

ISBN: (纸本)9781479974344

A fast image stitching algorithm based on improved speeded up robust feature (surf) is proposed to overcome the real-time performance and robustness of the original surf based stitching algorithms. The machine learning method is adopted to build a binary classifier, which identify the key feature points extracted by surf and remove the non-key feature points. In addition, the RELIEF-F algorithm is used for dimension reduction and simplification of the improved surf descriptor to achieve image registration. The threshold-based weighted fusion algorithm is used to achieve seamless image stitching. Finally, several experiments are conducted to verify the real-time performance and robustness of the improved algorithm.

关键词： fast image stitching surf algorithm machine learning RELIEF-F algorithm image fusion

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An Improved Image matching algorithm based on surf and Delaunay TIN

An Improved Image matching algorithm based on SURF and Delau...

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International Conference on Intelligent Earth Observing and Applications (IEOAs)

作者： Cheng Yuan-ming Cheng Peng-gen Chen Xiao-yong Zheng Shou-zhu E China Inst Technol Fac Geomat Nanchang 330013 Jiangxi Peoples R China Nanchang Inst Urban Planning & Survey Nanchang 330038 Jiangxi Peoples R China Guangxi Key Lab Spatial Informat & Geomat Guilin 541004 Guangxi Peoples R China

ISBN: (纸本)9781510600492

Image matching is one of the key technologies in the image processing. In order to increase its efficiency and precision, a new method for image matching which based on the improved surf and Delaunay-TIN is proposed in this paper. Based on the original surf algorithm, three constraint conditions, color invariant model, Delaunay-TIN, triangle similarity function and photography invariant are added into the original surf model. With the proposed algorithm, the image color information is effectively retained and the erroneous matching rate of features is largely reduced. The experimental results shows that this proposed method has the characteristics of higher matching speed, uniform distribution of feature points to be matched, and higher correct matching rate than the original algorithm does.

关键词： Image matching surf Delaunay-TIN invariant Image matching surf algorithm Delaunay-TIN Color invariant Triangle similarity function Photography invariant

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Pose detection of parallel robot based on improved Hough-K-means and surf algorithms

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JOURNAL OF ENGINEERING-JOE 2019年第22期2019卷 8324-8329页

作者： Zhang, Qian Gao, Guoqin Liu, Mengru Jiangsu Univ Sch Elect & Informat Engn Zhenjiang Jiangsu Peoples R China

It is difficult to detect end pose of auto electrocoating conveying parallel robot based on binocular vision because of less features, noise and blurred edges in image. So a pose detection method is presented. Firstly, according to distance and similarity between image points, the bilateral filtering is adopted to reduce noise. Secondly, for extracting straight lines on blurred edges and feature points in lines accurately, a Hough-K-means algorithm using K-means clustering analysis in parameter space after Hough transform is proposed. Thirdly, the discrete Gaussian-Hermite moment is used as feature descriptor to solve the low accuracy problem of principal directions of feature points described by speeded-up robust features (surf) descriptor. The extracted feature points are selected according to the similarity metric between constructed feature vectors. Finally, the vision model is developed to calculate the three-dimensional pose parameters of parallel robot based on obtained point pairs. The experiment results show that, compared with the surf algorithm, the average matching time decreases by 21.58%, the average deviations of detected poses in x, z and beta decrease by 1.149 mm, 0.646 mm and 1.164 degrees respectively by using the proposed method. The speed and accuracy of pose detection of parallel robot can be improved.

关键词： pattern clustering feature extraction pose estimation edge detection Hough transforms robot vision image restoration image denoising image filtering parallel robot surf algorithm auto electrocoating binocular vision blurred edges pose detection method Hough transform discrete Gaussian-Hermite moment extracted feature points Hough-K-means algorithm K-means clustering analysis speeded-up robust features descriptor

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Reconfigurable hardware architecture for faster descriptor extraction in surf

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ELECTRONICS LETTERS 2018年第4期54卷 210-212页

作者： Kim, Y. Jung, H. Sookmyung Womens Univ Dept Comp Sci Seoul South Korea

Speeded up robust features (surfs) are considered to be the most efficient feature extraction algorithm and it has been implemented in powerful hardware for real-time operation due to its characteristics of data-intensive computation of high complexity. Especially, the computational load of the descriptor extraction procedure is very significant and the overall performance of surf can be improved by speeding up the descriptor extraction step with increasing parallel hardware accelerators. However, simply increasing the hardware accelerators is burdensome because of causing significant area and power consumption. Therefore, a reconfigurable hardware architecture is proposed that enables achieving the maximum performance of the descriptor extraction step with making the best use of the existing accelerators without any additional ones. Experimental results show that the proposed architecture improves the performance of the descriptor extraction step by 24.77-47.45% with negligible area overheads when compared with the existing hardware implementations of the surf algorithm.

关键词： real-time systems feature extraction reconfigurable architectures reconfigurable hardware architecture descriptor extraction procedure speeded up robust features feature extraction algorithm real-time operation data-intensive computation computational load parallel hardware accelerators surf algorithm

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MDGHM-surf: A robust local image descriptor based on modified discrete Gaussian-Hermite moment

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PATTERN RECOGNITION 2015年第3期48卷 670-684页

作者： Kang, Tae-Koo Choi, In-Hwan Lim, Myo-Taeg Korea Univ Sch Elect Engn Seoul 136713 South Korea

This paper proposes a novel family of local feature descriptors, a variant of the speed up robust features (surf) descriptor, which is capable of demonstrably better performance. The conventional surf descriptor is an efficient implementation of the SIFT descriptor. Although the surf descriptor can represent the nature of the underlying image pattern, it is still sensitive to more complicated deformations such as large viewpoint and rotation changes. To solve this problem, our family of descriptors, called MDGHM-surf, is based on the modified discrete Gaussian-Hermite moment (MDGHM), which devises a movable mask to represent the local feature information of non-square images. Whereas conventional surf uses first-order derivatives, MDGHM-surf uses MDGHM, which offers more feature information than first-order derivative-based local descriptors such as surf and SIFL Consequently, by redefining the conventional surf descriptor using MDGHM, MDGHM-surf can extract more distinctive features than conventional surf. The results of evaluations conducted with six types of deformations indicate that our proposed method outperforms the matching accuracy of other surf related algorithms. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Modified discrete Gaussian-Hermite moment Local feature extraction surf algorithm

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Strategies of Improving Matching Accuracy about surf 1

Strategies of Improving Matching Accuracy about SURF

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1st International Conference on Electronics Instrumentation & Information Systems (EIIS)

作者： Quan Wei Liu Qiao Han Cheng Xue Yaohong Li Hua Changchun Univ Sci & Technol Sch Comp Sci & Technol Changchun Jilin Peoples R China

ISBN: (纸本)9781538608432

Speeded-Up Robust Features(surf) algorithm is a very popular matching method which are often used in fields such as feature extraction, fast image matching, depth map calculation and so on. About this algorithm, researches mainly focuses on improving the matching accuracy without increasing the matching time. In this paper, we mainly study on surf algorithm, and based on which three kinds of improving strategies are discussed. They are Lowe optimization algorithm, the descriptor dimension extension algorithm and the direct optimization method. Experimental results show that Lowe optimization method has the highest accuracy under different situations, and the descriptor dimension extension algorithm will be a good choice too, if the mismatching points can be removed effectively.

关键词： surf algorithm matching accuracy Lowe algorithm descriptor dimension extension image matching

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