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OS-PSO: A Modified Ratio of Exponentially Weighted Averages-Based Optical and SAR Image Registration

SENSORS 2024年第18期24卷 5959页

作者： Zhang, Hui Song, Yu Hu, Jingfang Li, Yansheng Li, Yang Gao, Guowei Beijing Informat Sci & Technol Univ Beijing Key Lab Sensor Beijing 100101 Peoples R China Beijing Informat Sci & Technol Univ Key Lab Modern Measurement & Control Technol Minist Educ Beijing 100192 Peoples R China Chinese Acad Sci Aerosp Informat Res Inst State Key Lab Transducer Technol Beijing 100190 Peoples R China

Optical and synthetic aperture radar (SAR) images exhibit non-negligible intensity differences due to their unique imaging mechanisms, which makes it difficult for classical sift-based algorithms to obtain sufficiently correct correspondences when processing the registration of these two types of images. To tackle this problem, an accurate optical and SAR image registration algorithm based on the sift algorithm (OS-PSO) is proposed. First, a modified ratio of exponentially weighted averages (MROEWA) operator is introduced to resolve the sudden dark patches in SAR images, thus generating more consistent gradients between optical and SAR images. Next, we innovatively construct the Harris scale space to replace the traditional difference in the Gaussian (DoG) scale space, identify repeatable key-points by searching for local maxima, and perform localization refinement on the identified key-points to improve their accuracy. Immediately after that, the gradient location orientation histogram (GLOH) method is adopted to construct the feature descriptors. Finally, we propose an enhanced matching method. The transformed relation is obtained in the initial matching stage using the nearest neighbor distance ratio (NNDR) and fast sample consensus (FSC) methods. And the re-matching takes into account the location, scale, and main direction of key-points to increase the number of correctly corresponding points. The proposed OS-PSO algorithm has been implemented on the Gaofen and Sentinel series with excellent results. The superior performance of the designed registration system can also be applied in complex scenarios, including urban, suburban, river, farmland, and lake areas, with more efficiency and accuracy than the state-of-the-art methods based on the WHU-OPT-SAR dataset and the BISTU-OPT-SAR dataset.

关键词： image registration sift algorithm MROEWA enhanced matching method

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Recognition and location of typical automotive parts based on the RGB-D camera

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COMPLEX & INTELLIGENT SYSTEMS 2021年第4期7卷 1759-1765页

作者： Liu, Wei Li, Fengpeng Jing, Cheng Wan, Yidong Su, Beibei Helali, M. Yancheng Inst Technol Sch Automot Engn Yancheng 221051 Jiangsu Peoples R China Jiangsu Coastal Inst New Energy Vehicle Yancheng 221051 Jiangsu Peoples R China

Aiming at the problem that the accuracy of multi-part automatic assembly line sorting is not high, a set of machine vision-based recognition and positioning system is designed with KINECT as the RGB-D camera. The internal and external parameters of the RGB-D camera were calibrated using MATLAB;taking the automobile tire as the target part, because it is better for the system and more accurate, the feature invariant feature transformation (sift) algorithm is used to extract and match the feature points of the target part. The depth-based image obtains the spatial position parameters of the target part, thereby calculating the three-dimensional coordinates of the target part, and realizes the recognition and positioning functions of the system. The experimental results show that the visual positioning effectiveness is 96% in the unstructured indoor environment, and the system has good robustness and real-time performance.

关键词： RGB-D camera Recognition and location sift algorithm Automatic assembly line

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Improved Point Cloud Registration with Scale Invariant Feature Extracted

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JOURNAL OF RUSSIAN LASER RESEARCH 2021年第2期42卷 219-225页

作者： Hu, Qinglong Niu, Jiayu Wang, Zhiwei Wang, Shifeng Changchun Univ Sci & Technol Natl Demonstrat Ctr Expt Optoelect Engn Educ 7089 Weixing Rd Changchun 130022 Jilin Peoples R China Changchun Univ Sci & Technol Key Lab Optoelect Measurement & Opt Informat Tran 7089 Weixing Rd Changchun 130022 Jilin Peoples R China

The efficiency and accuracy of point set registration is always a challenge to deal with. In this paper, we propose an improved algorithm using a scale invariant feature extracted. The larger transformation scale and rotation angle cause lower registration accuracy. The initial corresponding point set can be obtained using a scale invariant feature transform (sift) operator. In addition, the geometric features of the points are combined to remove the wrong points. The unit quaternion algorithm is used to estimate the best rigid body transformation matrix for precise registration. The experiments show that the registration accuracy increases by 7.99%, while the time consumption decreased by 6.24% in a typical indoor scene.

关键词： registration sift algorithm geometric features

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Research on the application of intelligent virtual simulation technology in the display of art works

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Applied Mathematics and Nonlinear Sciences 2024年第1期9卷

作者： Xie, Chi Li, Jianxun Wuhan Sports University Hubei Wuhan430079 China Hebei University Hebei Baoding071000 China

In this paper, the sift algorithm is used to detect as well as match the feature points of the artwork, select the centroid of the artwork as well as the support domain, and produce locally approximated surfaces in the support domain to perform a 1:1 virtual reconstruction of the artwork. To flesh out the presentation of the artwork, the images of the modeled artwork are encoded and decoded using Gaussian kernel functions, convolutional layers, and channel attention. The loss function is also optimized, and an end-to-end approach is used to generate the images. After analysis, it is concluded that the display characteristics of different artworks in the intelligent virtual simulation technology for artwork display are over 80%, among which all display characteristics of fresco works are over 90%, and the interaction degree as well as the humanity degree are also over 90%. Therefore, based on this technology, the artworks can be displayed well. © 2023 Chi Xie and Jianxun Li, published by Sciendo.

关键词： Artwork display Gaussian kernel function Intelligent virtual simulation sift algorithm Virtual reconstruction

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Interferometric phase diagram generation method based on dot trace texture information and semantic segmentation of correlation coefficients

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GEOCARTO INTERNATIONAL 2024年第1期39卷

作者： Zhang, Xuelin Wang, Zhaoxia Zhang, Hui Xie, Dongliang Inner Mongolia Univ Coll Elect Informat Engn Hohhot Peoples R China Inner Mongolia Univ Technol Coll Elect Power Hohhot Peoples R China Minist Educ Engn Res Ctr Large Energy Storage Technol Hohhot Peoples R China Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China

This paper proposes a method for generating interferometric phase diagrams, which includes interferometric image registration based on Dot Trace Texture Information (DTTI) and interferometric phase filtering based on semantic segmentation. First, the InSAR images are sharpened according to the different backscattering characteristics of various pixel values, and DTTI is extracted to generate the Dot Trace Texture Map (DTTM). Second, sift feature points are extracted from two InSAR coherent complex images. They are then screened by comparison with DTTI. These selected points are used to calculate the registration relationship, ensuring precise registration of the two images. Third, the interferometric phase diagram is segmented by semantics based on correlation coefficients. For high-quality interferometric phase regions, we use two-dimensional frequency domain rotational symmetric Gaussian Laplace and wavelet domain filters successively. For low-quality regions, we use an average filter to smooth out noise. The superiority of the proposed algorithm was verified through comparative experiments.

关键词： Dot trace texture information image registration sift algorithm semantic segmentation interferometric phase filtering

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High-speed and Accurate Method for the Gear Defect Detection based on OpenCV 22

High-speed and Accurate Method for the Gear Defect Detection...

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Proceedings of the 2022 5th International Conference on Telecommunications and Communication Engineering

作者： Jianan Li Wugang Lai Fanqiang Lin College of Mechanical and Electrical Engineering Chengdu University of Technology China

ISBN: (纸本)9781450397797

Gear defect detection is considered to be a vital technology in current equipment applications. Since traditional gear defect detection is generally determined by the direct human eye of the production employees, it will definitely lead to uncertainty caused by numerous subjective variables, and the efficiency is also low. Based on this, this article provides a gear defect identification and detection technique based on image technology and OpenCV, to achieve the objective of rapidly and correctly determining if the gear has defects, and at the same time, the approach is confirmed by combining hardware equipment. Combined with industrial cameras, photos of various types of gears are gathered and tested on the simulation platform. The detection time is all within 1s, and the detection accuracy of plastic gears is above 90%. Compared with existing detection methods, the proposed method presents more obvious advantages in terms of accuracy and efficiency.

关键词： sift algorithm Contour detection Gauss-Laplace pyramid algorithm Gear defect detection Hu moment

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Design and Application of PET Bottle Defect Detection and Control System 22

Design and Application of PET Bottle Defect Detection and Co...

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Proceedings of the 5th International Conference on Information Technologies and Electrical Engineering

作者： Dan Li Qiaoni Zhao Jinyan Shi Yongchao Xie Hunan Railway Professional Technology College China

ISBN: (纸本)9781450396806

According to the demand of PET bottle defect detection in actual production, the framework of the whole detection system is analyzed, and according to the production demand, each module of the PET bottle defect detection and control system is designed. Firstly, the hardware part of the detection system is designed. The hardware system is divided into several subsystems, such as mechanical transmission system, image acquisition system and bottle removal system. Through the establishment of the hardware platform, the system can realize the functions of automatic image collection, automatic analysis and judgment, and automatic elimination of unqualified bottles. Secondly, sift algorithm is used to design the software system to achieve accurate image matching and automatic detection of PET bottle defects. Finally, the system is applied to the actual PET bottle production line, the research and experimental results show that: the system for PET bottle defect detection accuracy of 99%.

关键词： sift algorithm Image recognition Automatic detection

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Image feature extraction algorithm in big data environment

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2020年第4期39卷 5109-5118页

作者： Zhang, Yubao Zhejiang Fash Inst Technol Sch Informat Media Ningbo 315211 Zhejiang Peoples R China

The purpose of this article is to explore effective image feature extraction algorithms in the context of big data, and to mine their potential information from complex image data. Based on the BRISK and sift algorithms, this paper proposes an image feature extraction and matching algorithm based on BRISK corner points. By combining the sift scale space and the BRISK algorithm, a new scale space construction method is proposed. The BRISK algorithm extracts the corner invariant features. Then, by using the improved feature matching method and eliminating the mismatching algorithm, the exact matching of the images is realized. A large number of experimental verifications were performed in the standard test Mikolajczyk image database and aerial image database. The experimental results show that the improved algorithm in this paper is an effective image matching algorithm. The highest accuracy of actual aerial image matching can reach 85.19%, and it can realize the actual aerial image matching that BRISK and sift algorithms cannot complete. The improved algorithm in this paper has the advantages of higher matching accuracy and strong robustness.

关键词： Big data image feature extraction corner point brisk algorithm sift algorithm

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Fast detection of moving objects based on sequential images processing

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2020年第4期39卷 5037-5044页

作者： Wei, Peng-Cheng He, Fangcheng Li, Jing Chongqing Univ Educ Sch Math & Informat Engn Chongqing Peoples R China Chongqing Univ Educ Coll Foreign Languages Literature Chongqing Peoples R China

Nowadays, moving object detection in sequence images has become a hot topic in computer vision research, and has a very wide range of practical applications in many fields of military and daily life. In this paper, fast detection of moving objects in complex background is studied, and fast detection methods for moving objects in static and dynamic scenes are proposed respectively. Firstly, based on image preprocessing, aiming at the difficulty of feature extraction of moving targets in low illumination at night, Gamma change is used to process. Secondly, for the fast detection of moving objects in static scenes, this paper designs a detection method combining background difference and edge frame difference. Finally, aiming at the fast detection of moving objects in dynamic scenes, a feature matching detection method based on the sift algorithm is designed in this paper. Simulation experiments show that the method designed in this paper has good detection performance.

关键词： Sequence image fast detection of moving objects Gamma change sift algorithm

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GF-2 Panchromatic and Multispectral Remote Sensing Image Registration algorithm

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IEEE ACCESS 2020年 8卷 138067-138076页

作者： Wang, Sen Wang, Xiaofei Li, Jianxiong Heilongjiang Univ Coll Elect Engn Harbin 150080 Peoples R China

Image registration is an important step in remote sensing image preprocessing. The accuracy, efficiency, and automatic degree of image registration will directly affect the results of subsequent image processing and analysis. Due to the slow registration speed and low registration accuracy of sift algorithm for GF-2 panchromatic and multispectral remote sensing images, sift algorithm is improved in this article to improve the efficiency of image registration algorithm. In this article, the strategy of information entropy meshes is introduced, and feature extraction is carried out only for the regions with large information entropy, so that the running time of feature extraction can be reduced. By introducing Canny operator to eliminate the unstable edge response points, the number of feature points can be further reduced, thus the computation amount of the algorithm can be also reduced. Due to the poor registration effect of sift algorithm for remote sensing images, a new gradient calculation method and feature description method are used in this article to enhance the robustness of feature descriptors. In the feature matching stage, this article proposes a two-layer matching strategy, which uses mutual Euclidean distance for initial matching, then uses FSC algorithm for fine matching, and finally realizes the registration of GF-2 panchromatic and multispectral remote sensing images. Experimental results show that the proposed algorithm can obtain more correct matching point pairs when the number of extracted feature points is small. Moreover, the registration accuracy and speed are both higher than the comparison algorithm. This article uses the remote sensing images of urban scenes dominated by plains and mountainous scenes with small terrain fluctuation respectively for experiments. The algorithm in this article can achieve registration accuracy better than 0.5 pixels, and in terms of time consumption, it is only about 70% of sift algorithm, and the computational

关键词： GF-2 image registration sift algorithm information entropy FSC algorithm

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