检索结果-内蒙古大学图书馆

作者： Lijin Deng Yan Piao Shuo Liu Changchun Univ.of Sci.&Tech.Changchun of Jilin CETC52 Hangzhou of Zhejiang

The difference of sensor devices and the camera position offset will lead the geometric differences of the matching images. The traditional sift image matching algorithm has a large number of incorrect matching point pairs and the matching accuracy is low during the process of image matching. In order to solve this problem, a sift image matching based on Maximum Likelihood Estimation Sample Consensus(MLESAC) algorithm is proposed. Compared with the traditional sift feature matching algorithm, SURF feature matching algorithm and RANSAC feature matching algorithm, the proposed algorithm can effectively remove the false matching feature point pairs during the image matching process. Experimental results show that the proposed algorithm has higher matching accuracy and faster matching efficiency.

关键词： Image matching sift algorithm MLESAC algorithm matching accuracy

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Research on Dimensional Measurement Method of Large Parts 2019

Research on Dimensional Measurement Method of Large Parts

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Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering

作者： Dongri Shan Jiancong Xu School of Electronic and Information Engineering Qi lu University of Technology (Shan dong Academy of Sciences) Jinan Shan dong School of Mechanical and Automotive Engineering Qi lu University of Technology (Shan dong Academy of Sciences) Jinan Shan dong

ISBN: (纸本)9781450372930

Firstly, the size definition of large parts is given, and the importance of large-scale part size measurement methods is analyzed. Then, the existing large-scale parts measurement methods are studied, including large-scale three-coordinate measurement method, double theodolite measurement method, and laser. Tracker measurement method, indoor GPS measurement method and machine vision measurement method. The measurement principle, structure composition and research status of each measurement method are analyzed and summarized, and the sift image mosaic algorithm is introduced. Finally, the research and development trend of large-scale part size measurement methods is prospected.

关键词： Large parts sift algorithm Dimensional measurement Machine vision Coordinate measuring machine

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Improved Frame Difference algorithm Based on CNN for Moving Target Detection

Improved Frame Difference Algorithm Based on CNN for Moving ...

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第三十九届中国控制会议

作者： Xuanxuan Cui Weibin Zhang Dan Liu Nanjing University of Science and Technology School of Electronic and Optical Engineering Nanjing University of Science and Technology School of Computer Engineering Chang'an University School of Economics and Management

In order to improve the shortcomings of frame difference method in moving target detection and improve the accuracy and robustness of moving target detection,an improved frame difference method based on CNN is ***,in order to solve the problem of blind spot in autopilot and improve the safety of autopilot,sift algorithm is used to obtain the panoramic image of moving ***,frame difference method is adopted to obtain the foreground image,and then CNN is used to repair the foreground ***,sift is used to splicing the restored foreground image to obtain the panoramic image of the foreground *** simulation results show that the proposed algorithm is effective,efficient and accurate in the extraction and repair of moving *** the proposed method,a complete panoramic image of moving targets can be obtained.

关键词： Autopilot sift algorithm CNN Panoramic Image Object Contour Extraction

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Image matching with sift feature 2

Image matching with SIFT feature

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2nd International Conference on Inventive Systems and Control (ICISC)

作者： Satare, Rajkumar N. Khot, S. R. DY Patil Coll Engn & Technol Dept Elect & Telecommun Kolhapur Maharashtra India

ISBN: (纸本)9781538608074

An image matching algorithm is present in this paper. A set of interest points known as sift features are computed for a pair of images. Every keypoint has a descriptor based on histogram of magnitude and direction of gradients. These descriptors are the primary input for the image correspondence algorithm. Initial probabilities are assigned for categories considering a feature point assignment to one of the category as a classification problem. For selecting the neighbours for the left keypoint, a fixed number of pixels around the keypoint, considered as a window, are selected. The neighbours of the right keypoint are based on inspection of pair of images and the disparity range. The probabilistic estimates are iteratively improved by a relaxation labeling technique. The neighbour keypoints which will contribute to improve the probability is based on consistency property

关键词： Images keypoints sift algorithm

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Three-dimensional digital reconstruction of skin epidermis and dermis

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JOURNAL OF MICROSCOPY 2018年第2期270卷 170-175页

作者： Liu, P. Zhu, J. -Y. Tang, B. Hu, Z. -C. Guangzhou Red Cross Hosp Guangzhou Guangdong Peoples R China Sun Yat Sen Univ Affiliated Hosp 1 Guangzhou Guangdong Peoples R China

This study describes how three-dimensional (3D) human skin tissue is reconstructed, and provides digital anatomical data for the physiological structure of human skin tissue based on large-scale thin serial sections. Human skin samples embedded in paraffin were cut serially into thin sections and then stained with hematoxylin-eosin. Images of serial sections obtained from lighting microscopy were scanned and aligned by the scale-invariant feature transform algorithm. 3D reconstruction of the skin tissue was generated using Mimics software. Fibre content, porosity, average pore diameter and specific surface area of dermis were analysed using the ImageJ analysis system. The root mean square error and mutual information based on the scale-invariant feature transform algorithm registration were significantly greater than those based on the manual registration. Fibre distribution gradually decreased from top to bottom;while porosity showed an opposite trend with irregular average pore diameter distribution. A specific surface area of the dermis showed a V' shape trend. Our data suggested that 3D reconstruction of human skin tissue based on large-scale serial sections could be a valuable tool for providing a highly accurate histological structure for analysis of skin tissue. Moreover, this technology could be utilized to produce tissue-engineered skin via a 3D bioprinter in the future. Lay description This study is to reconstruct three-dimensional (3D) structure of the skin tissue to clarify the physiology of the skin tissue and to provide the anatomical data for 3D bio printer based on large scale serial skin tissue slices. Normal lateral thigh skin tissue were collected and processed to be a serial sections stained with hematoxylin-eosin. Whole serial slides were digitized by scanned lighting microscopy and aligned by the scale-invariant feature transform algorithm. Mimics software were used to generate 3D reconstructions of the skin tissue. Image analysis system was pe

关键词： Serial sections sift algorithm 3D reconstruction skin tissue

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Research on power equipment recognition method based on image processing

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EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING 2019年第1期2019卷 1页

作者： Wang, Haiyan Meng, Fanwei Changchun Sci Tech Univ Changchun Jilin Peoples R China

Electric energy is an indispensable energy in life, and the power network is the basis to ensure its normal circulation, in which the operation status of power equipment is one of the key factors to determine the safe and stable operation of the power network. In the information age, the traditional manual periodic inspection and the existing method of relying on manual monitoring equipment operation status can no longer meet the needs of safe operation of equipment;relying on computer technology and image recognition technology to achieve automatic identification of power equipment has become a research hot spot. In order to realize automatic identification of power equipment, this paper presents a method of recognition of power equipment based on image processing. Firstly, the power equipment image is preprocessed by various denoising and sharpening algorithms to remove the noise and distortion of the image and improve the image quality;secondly, the sift algorithm is used to extract image features, and PCA algorithm is used to reduce the dimension;finally, the support vector machine is used to classify and recognize the image. The simulation results show that the proposed denoising and sharpening algorithms can process images well and improve the quality of images. The support vector machine is used to classify the image features processed by sift algorithm and PCA algorithm, and the automatic recognition of power equipment is realized. And the method of power identification based on image processing proposed in this paper has good recognition accuracy.

关键词： Power equipment Image processing sift algorithm PCA algorithm Support vector machine

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Improved image matching method based on cursory search and detail-oriented correction with extension window

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MULTIMEDIA TOOLS AND APPLICATIONS 2018年第21期77卷 28885-28904页

作者： Huo, Fengcai Wang, Di Ren, Weijian Du, Ying Northeast Petr Univ Sch Elect Informat Engn Daqing 163318 Peoples R China China Power Puhua Informat Technol Co Ltd Beijing 100085 Peoples R China

In order to achieve the fast and accurate image matching, gray matching algorithm and sift feature matching algorithm are combined, and an approach to the cursory search and detail-oriented correction with extension window is proposed. The cursory search is achieved by using new adaptive optimal guidance artificial bee colony algorithm (AOGABC) instead of ergodicity of the traditional gray matching algorithm. The gray correlation degree with statistical properties serves as the fitness function of the artificial colony algorithm (ABC). The extensional image window has built after cutting image according to the extension rules in extension window, detail-oriented correction accurately matches image by using the sift algorithm. The experiments verify that the matching method not only realizes rapidity because of performance of artificial bee colony algorithm and gray relational grade in the cursory search, but also achieves matching accuracy resulted from the combination of sift algorithm and extension window in this paper. By comparing the effects of different algorithms in the typical image, the results show that the purpose of the exact match is achieved.

关键词： Adaptive optimal guidance Artificial bee Colony algorithm Gray relation analysis Extension window sift algorithm Image matching

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An Approach to 3D Building Model Retrieval Based on Topology Structure and View Feature

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IEEE ACCESS 2018年 6卷 31685-31694页

作者： Liu, Tao Gao, Jin Zhao, Yuchen Zhejiang Univ State Key Lab CAD&CG Hangzhou 310058 Zhejiang Peoples R China North Univ China Coll Big Data Taiyuan 030051 Shanxi Peoples R China China Waterborne Transport Res Inst Beijing 100088 Peoples R China

This paper proposes an approach to 3-D building model retrieval based on a topology structure and view feature using two filter steps to finish the building model retrieval. First, the distance transformation method is used to extract the topological structure of 3-D building models. The obtained skeleton points of 3D building models are classified by our concentric sphere method. The 3-D building models are then filtered for a first time based on the distribution features. Second, 3-D building models are projected onto 2-D images from the viewpoints of skeleton points. The scale-invariant feature transform algorithm is used to extract feature points from 2-D projection images, and the idea of the bag of feature method is used to compare the projection images. The 3-D building models are then filtered for a second time. Finally, we can get the retrieval result (the matched models). This method first carries out the matching of the overall structure and then carries out the matching of local details. This conforms to the cognitive style of human. In addition, the experiment results show the effectiveness of our method.

关键词： 3D building model retrieval topology structure view feature distance transformation sift algorithm

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A Cerebrovascular Image Segmentation Method Based on Geometrical Feature Point Clustering and Local Threshold

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CURRENT MEDICAL IMAGING REVIEWS 2018年第5期14卷 748-770页

作者： Liu, Bin Zhu, Chen Qu, Xiaofeng Wang, Mingzhe Zhang, Song Wang, Yi Fan, Xin Luo, Zhongxuan Zhang, Bingbing Yue, Zongge Dalian Univ Technol Int Sch Informat Sci & Engn DUT RUISE Dalian Peoples R China Dalian Univ Technol Key Lab Ubiquitous Network & Serv Software Liaoni Dalian Peoples R China Chinese Acad Sci Inst Comp Technol Beijing Peoples R China Dalian Med Univ Hosp 2 Dalian Peoples R China Dalian Med Univ Modern Technol & Educ Dept Dalian Peoples R China Dalian Univ Technol Affiliated Hosp Dalian Peoples R China

Background: For the cerebrovascular Digital Subtraction Angiography (DSA), how to restrain the patient motion artifact to improve the quality of subtraction image has an important effect on the clinical diagnosis. Methods: Currently, image registration is the main way to extract the blood vessels. However, there is usually massive calculation in the registration process. And it is usually only suitable for simple rigid motion artifact. Instead of registration way, a novel cerebrovascular segmentation method was proposed to extract blood vessels in this paper. In this method, the geometrical feature points of mask image and live image were firstly detected by sift algorithm under same restrain parameters. Secondly, the feature points were clustered and the subtraction of clustered point set was implemented. Then, the coordinates of the residual feature points were adjusted based on gray gradient. Lastly, the vessel image was segmented based on region growing and local threshold. Result: Experiments for the sequential cerebrovascular DSA images illustrate the applicability of this method. The quality of the vessel image after segmentation was satisfactory. The interdependency of geometrical feature information for both mask image and live image was adequately utilized in this new method. Conclusion: This method can provide accurate vessel image data for the clinical operation based on DSA interventional therapy.

关键词： Digital subtraction angiography cerebrovascular image segmentation feature point clustering local threshold sift algorithm DSA interventional therapy

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An Improved sift Matching algorithm

An Improved SIFT Matching Algorithm

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International Conference on Measurement, Instrumentation and Automation (ICMIA 2012)

作者： Ding Can Qu Chang-wen Su Feng Naval Aeronaut & Astronaut Univ Dept Elect & Informat Engn Yantai 264001 Peoples R China

ISBN: (纸本)9783037855454

The high dimension and complexity of feature descriptor of Scale Invariant Feature Transform (sift), not only occupy the memory spaces, but also influence the speed of feature matching. We adopt the statistic feature point's neighbor gradient method, the local statistic area is constructed by 8 concentric square ring feature of points-centered, compute gradient of these pixels, and statistic gradient accumulated value of 8 directions, and then descending sort them, at last normalize them. The new feature descriptor descend dimension of feature from 128 to 64, the proposed method can improve matching speed and keep matching precision at the same time.

关键词： sift algorithm image matching feature descriptor DOG

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