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Ice Velocity in Upstream of Heilongjiang Based on UAV Low-Altitude Remote Sensing and the SIFT algorithm

WATER 2022年第12期14卷 1957-1957页

作者： Wang, Enliang Hu, Shengbo Han, Hongwei Li, Yuang Ren, Zhifeng Du, Shilin Northeast Agr Univ Sch Water Conservancy & Civil Engn Harbin 150030 Peoples R China Heilongjiang Prov Key Lab Water Resources & Water Harbin 150030 Peoples R China

In river management, it is important to obtain ice velocity quickly and accurately during ice flood periods. However, traditional ice velocity monitoring methods require buoys, which are costly and inefficient to distribute. It was found that UAV remote sensing images combined with machine vision technology yielded obvious practical advantages in ice velocity monitoring. Current research has mainly monitored sea ice velocity through GPS or satellite remote sensing technology, with few reports available on river ice velocity monitoring. Moreover, traditional river ice velocity monitoring methods are subjective. To solve the problems of existing time-consuming and inaccurate ice velocity monitoring methods, a new ice velocity extraction method based on UAV remote sensing technology is proposed in this article. In this study, the Mohe River section in Heilongjiang Province was chosen as the research area. High-resolution orthoimages were obtained with a UAV during the ice flood period, and feature points in drift ice images were then extracted with the scale-invariant feature transform (SIFT) algorithm. Moreover, the extracted feature points were matched with the brute force (BF) algorithm. According to optimization results obtained with the random sample consensus (ransac) algorithm, the motion trajectories of these feature points were tracked, and an ice displacement rate field was finally established. The results indicated that the average ice velocities in the research area reached 2.00 and 0.74 m/s, and the maximum ice velocities on the right side of the river center were 2.65 and 1.04 m/s at 16:00 on 25 April 2021 and 8:00 on 26 April 2021, respectively. The ice velocity decreased from the river center toward the river banks. The proposed ice velocity monitoring technique and reported data in this study could provide an effective reference for the prediction of ice flood disasters.

关键词： unmanned aerial vehicles SIFT algorithm brutal force matching ransac algorithm ice velocity

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An Improved ASIFT Image Feature Matching algorithm Based on POS Information

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SENSORS 2022年第20期22卷 7749-7749页

作者： Gao, Junchai Sun, Zhen Xian Technol Univ Sch Elect Informat Engn Xian 710021 Peoples R China

The affine scale-invariant feature transform (ASIFT) algorithm is a feature extraction algorithm with affinity and scale invariance, which is suitable for image feature matching using unmanned aerial vehicles (UAVs). However, there are many problems in the matching process, such as the low efficiency and mismatching. In order to improve the matching efficiency, this algorithm firstly simulates image distortion based on the position and orientation system (POS) information from real-time UAV measurements to reduce the number of simulated images. Then, the scale-invariant feature transform (SIFT) algorithm is used for feature point detection, and the extracted feature points are combined with the binary robust invariant scalable keypoints (BRISK) descriptor to generate the binary feature descriptor, which is matched using the Hamming distance. Finally, in order to improve the matching accuracy of the UAV images, based on the random sample consensus (ransac) a false matching eliminated algorithm is proposed. Through four groups of experiments, the proposed algorithm is compared with the SIFT and ASIFT. The results show that the algorithm can optimize the matching effect and improve the matching speed.

关键词： UAV image feature matching ASIFT algorithm BRISK descriptor ransac algorithm

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BDS Multi-Frequency Soil Moisture Retrieval Considering the Amplitude Stability of Reflected Signal

BDS Multi-Frequency Soil Moisture Retrieval Considering the ...

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第十四届中国卫星导航年会

作者： Huiyi Xian Zhongpei Guan Fei Shen Xinyun Cao Yulong Ge School of Geographical Sciences Nanjing Normal University Key Laboratory of Virtual Geographic Environment (Nanjing Normal University) Ministry of Education Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application School of Marine Science and Engineering Nanjing Normal University

With the successful networking of BeiDou Navigation Satellite System（BDS）, BDS B1I/B2I/B3I signals enriched GNSS-IR data ***-IR technology used to monitor soil moisture content（SMC） is constantly developing, but there are still the following problems in the current ***, the elevation angle range used for inversion is mostly determined based on experience, ignoring the problem that the amplitude of reflected signal varies greatly within a certain elevation angle range due to the influence of antenna gain, soil roughness, which affects the inversion Performance;Secondly, using single-star data, the inversion accuracy of linear regression model established by least squares algorithm is poor. Therefore, this research proposed a BDS multi-frequency SMC inversion method that takes into account the amplitude stability of reflected signal. Based on the sliding window method, a stationary signal window is obtained intelligently as the data source for subsequent inversion. On this basis, joint inversion of multi-frequency signals is carried out. In addition, ransac algorithm is used to estimate model parameters to reduce noise interference. The experiment shows that（1） Using the window with stable amplitude change as the elevation angle range of the experiment is useful to improve the retrieval accuracy of SMC. Compared with the retrieval results of the empirical elevation angle range of 5°-30°, the correlation coefficient increases in the range of 5.2%-34.9%, and the root mean square error decreases in the range of 19.2%-52.9%;（2） B1I/B2I/B3I triple-frequency signal fusion can reflect the soil moisture information near the measurement station more comprehensively;（3） Compared with the least square linear regression algorithm, the SMC estimate effect of ransac algorithm is ***, the SMC was inverted using the delayed phase fusion of the BDS triple-frequency signal. The correlation coefficient can reach 0.9850, the root mean square error is 0.00

关键词： BDS-IR Reflected signal Amplitude Soil moisture Signal to noise ratio ransac algorithm

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Research on Binocular Visual System of Robotic Arm Based on Improved SURF algorithm

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IEEE SENSORS JOURNAL 2020年第20期20卷 11849-11855页

作者： Sheng, Haiyan Wei, Shimin Yu, Xiuli Tang, Ling Beijing Univ Posts & Telecommun Coll Automat Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Century Coll Beijing 100096 Peoples R China

With the increasingly extensive application of robots in industrial production, visual of the robotic arm has become an important research direction in the field of robots, which is also recognized as believed to widely considered to the most vital directions of modern high-tech development. In the robot vision system, the binocular visual system is most widely applied. When the robotic arm based on binocular vision captures the object, SURF algorithm is adopted to realize feature point extraction and matching of images. Because of the influence of the objective factors, there is false match in the process of SURF matching of feature points. In this paper, SURF algorithm is improved and reverse feature vectors matching strategy is used to initialize the matching points set. Then the ransac algorithm is adopted to select the initial matching points set in accordance of the polar geometric model to get the final good match set. The experiment results show that the improved SURF algorithm has higher registration accuracy and faster speed than SURF.

关键词： Feature extraction Cameras Robot sensing systems Service robots Visualization Machine vision Robotic arm binocular visual SURF algorithm ransac algorithm feature point matching

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Bridge Surface Damage Image Stitching Method Based on SURF algorithm 20

Bridge Surface Damage Image Stitching Method Based on SURF A...

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20th COTA International Conference of Transportation Professionals (CICTP) - Advanced Transportation, Enhanced Connection

作者： Da, Xingyu Wang, Xiali Yu, Xin Wang, Lihong Changan Univ Sch Informat Engn Xian 710064 Peoples R China

ISBN: (数字)9780784482933

ISBN: (纸本)9780784482933

With rapid road and bridge development, image-based crack detection technology has become important in current research. For large bridges, obtaining high-precision panoramic images is difficult. Therefore, image-stitching technology with mutual overlap rate producing high-definition images is crucial. In this paper, a low-overlap image mosaic method based on SURF was proposed, which calculates feature points of collected images with low overlap rate by SURF algorithm, then improves Harris operator to enhance angular point adaptability, followed by rough matching through 2 - NN, using ransac (Random Sample Consensus Random sampling uniformity) algorithm. eliminating wrong matching points to conduct accurate matching, and finally using multi-band fusion to solve excessive incoherence in joint-line and process image matching. The results show that image mosaics based on SURF have higher matching accuracy, adaptability, and robustness in the case of low overlap rate, which lays a foundation for further crack detection and has strong application value.

关键词： Image mosaic SURF algorithm ransac algorithm Multi-band fusion

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ransac lens boundary feature based kernel SVM for transparent contact lens detection

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IET BIOMETRICS 2019年第3期8卷 177-184页

作者： Kumar, Mohit Puhan, Niladri B. Indian Inst Technol Bhubaneswar Sch Elect Sci Bhubaneswar India

Transparent contact lens spoofing has been demonstrated to hamper the overall performance of an iris recognition system. Achieving high detection accuracy with transparent lens is quite challenging using iris texture analysis based techniques. In this regard, the authors propose a supervised learning based transparent lens detection method by designing a novel set of features to describe the faint lens boundary. The input image is first segmented for extracting salient edge points in the sclera region of interest. ransac algorithm then performs circle fitting to generate the set of R-points for feature computation. The novel features such as concentricity parameter, R-point count, R-point intensity, R-circle radius, R-cluster count and circle genuineness are associated with distinctive range of values for each class. Experimental results obtained using the kernel-support vector machine (SVM) classifier show that the proposed method can achieve higher average detection accuracy as compared to state-of-the-art techniques: 90.63% (NotreDame I), 84.5% (NotreDame II), 83% (IIIT-D Cogent) and 86.27% (IIIT-D Vista).

关键词： learning (artificial intelligence) support vector machines feature extraction image classification image texture image segmentation iris recognition contact lenses ransac lens boundary feature transparent contact lens detection iris recognition system iris texture analysis based techniques supervised learning transparent lens detection method ransac algorithm kernel-support vector machine

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Intelligent Interpretation of the Geometric Properties of Rock Mass Discontinuities Based on an Unmanned Aerial Vehicle

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FRONTIERS IN EARTH SCIENCE 2021年 9卷

作者： Chen, Na Du, Chang-jie Ding, Xiang Hubei Univ Technol Sch Civil Engn Architecture & Environm Wuhan Peoples R China Hubei Univ Technol Sino French Joint Res Collaborat Geomech & Concre Wuhan Peoples R China

The geometric properties of rock mass discontinuities are essential for the evaluation of the safety of rock masses. Numerous studies have recently been performed on the extraction of discontinuity information. However, most methods are characterized by poor data collection and processing efficiency. This paper presents a UAV-based methodology for the accurate and complete acquisition of rock surface data, as well as the automatic extraction of discontinuity information. Moreover, a program called Random Sample Consensus (ransac) Discontinuity Detection (RDD) is developed to extract discontinuity information based on the proposed method. The conclusions of this research are as follows. 1) ransac Discontinuity Detection (RDD) can identify the feature point set of discontinuities from a raw point cloud, and can calculate the discontinuity orientation. 2) The boundary of a discontinuity can be precisely depicted using the improved Graham scan algorithm. 3) The orientations of marked discontinuities extracted by RDD are compared with those extracted by the three-point method in CloudCompare. The differences in the orientations extracted by the two methods are found to be less than 3 degrees for flat discontinuities and only about 4.87 degrees for rough discontinuities, which are within a reasonable error range in practical engineering applications. Therefore, the feasibility of the proposed method is verified.

关键词： UAV technique point cloud automatic extraction discontinuity ransac algorithm

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Film and television industry cloud exhibition design based on 3D imaging and virtual reality

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DISPLAYS 2021年 70卷

作者： Zhuang, Kaige Dalian Med Univ Art Coll Dalian 116044 Peoples R China

The three-dimensional virtual scene can provide users with a visual three-dimensional virtual environment, with various multimedia channels such as sound, video, force feedback equipment, etc., to bring users a completely immersive interactive experience. This paper introduces 3D imaging and virtual reality technology in the film and television industry cloud exhibition, and develops a virtual display platform. First of all, this paper divides the registration into two processes: camera calibration and joint calibration of the camera and laser scanner based on the calibration results. Camera calibration can determine the plane model of the calibration board in the camera coordinate system, and the joint calibration uses the ransac algorithm to extract the point cloud of the plane model of the calibration board, and then optimizes the distance between the points in the plane model point cloud and the corresponding plane in the camera coordinate system Find the optimal transformation between the two sets of data, and then calculate the registration relationship between the point cloud and the image. Secondly, this article conducts a demand analysis of the film and television industry cloud exhibition platform based on virtual reality technology, including the business goals set by the platform, platform system analysis, overall design, and system operating environment and configuration requirements. This model provides a feasible solution for the visual interaction of the cloud exhibition design of the film and television industry.

关键词： Film and television industry Cloud exhibition 3D imaging Virtual reality ransac algorithm Point cloud matching

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Feature point matching of infrared and visible image 43

Feature point matching of infrared and visible image

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Conference on Applications of Digital Image Processing XLIII

作者： Li, Wuxin Chen, Qian Gu, Guohua Bai, Hong-yang Sui, Xiubao Nanjing Univ Sci & Technol Sch Elect Engn & Opt Engn Nanjing 210094 Jiangsu Peoples R China Nanjing Univ Sci & Technol Nanjing 210094 Jiangsu Peoples R China

ISBN: (数字)9781510638273

ISBN: (纸本)9781510638273

Feature point matching has been widely applied in image registration, image fusion, remote sensing and other fields. The relation between the pixels of infrared images and pixels of visible images is complex due to the images were taken by different sensors. Different sensors images also contain some common information which can been depended to achieve point matching. Scale Invariant Feature Transform (SIFT) algorithm is an effective and popular feature extraction algorithm. SIFT algorithm can be used in point matching, it can get feature descriptor vectors of the feature points which extracted from the images. But in some scenes, SIFT algorithm can't achieve the accurate feature point matching. Different from SIFT algorithm, Edge-Oriented-Histogram (EOH) algorithm characters the orientation information of the edge and EOH feature descriptor can integrate the boundary information in different directions around the feature points, so that we can realize the describe of the edge direction and amplitude by EOH algorithm. To achieve the accurate feature point matching of infrared image and visible image, we propose a feature point matching method based on SIFT algorithm and EOH algorithm. Firstly, we use image enhancement to increase contrast of the image and then we use SIFT algorithm to extract feature points. Next, we utilize the EOH algorithm to get the 80 bins descriptors of the feature points which detected by SIFT algorithm. We calculate Euclidean distance to get the similarity of the descriptors to achieve point matching. In order to improve the matching accuracy, we adopt Random Sample Consensus (ransac) algorithm to eliminate the mismatching points. Nevertheless, ransac can't get all correct points, we use another measure of Euclidean to select correct pairs, then we combine the two parts to match the feature points again. Experimental results demonstrate that our method can effectively improve the accuracy of matching and find more correct matching point pai

关键词： SIFT algorithm EOH descriptor Euclidean distance feature point matching mismatching points feature descriptor ransac algorithm second matching

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Cliff face rock slope stability analysis based on unmanned arial vehicle (UAV) photogrammetry

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GEOMECHANICS AND GEOPHYSICS FOR GEO-ENERGY AND GEO-RESOURCES 2019年第4期5卷 333-344页

作者： Wang, Shuhong Ahmed, Zulkifl Hashmi, Muhammad Zaffar Wang Pengyu Northeastern Univ Sch Resource & Civil Engn Shenyang 110819 Liaoning Peoples R China COMSATS Univ Islamabad Dept Meteorol Islamabad Pakistan

Rock cliff faces are mostly avoided in rock engineering research, especially where the scale of the slope exceeds the scale of fracturing present in the rock mass. The research to understand the rock cliff face joints plays an important role in slope engineering. This paper presents a rock block identification method based on unnamed aerial vehicle photogrammetry and its computer implementation of Cliff face rock, Fort Munro Pakistan. An advance bundle adjustment method was used to build the real three-dimensional (3D) surface model of the rock mass. Later, random sample consensus algorithm was used to search the structural planes in cloud point model. A computer program, geotechnical structure and model analysis (GeoSMA-3D) was developed to solve the engineering problems and to verify the example. The program confirmed the efficiency of the theory in dealing with complex surface modelling and cliff face rocky slope stability analysis. The approach presented can be applied as a general guiding design principle for cliff face rock slope.

关键词： Rock cliff face Block theory Bundle adjustment method ransac algorithm UAV photogrammetry

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