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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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Design of incomplete 3D information image recognition system based on sift algorithm and wireless network

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EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING 2020年第1期2020卷 1-20页

作者： Zhang Zhixin Jiang Shuhao Tianjin Univ Commerce Informat Engn Dept Tianjin 300134 Peoples R China

The traditional image recognition technology can transform some expression form of image into the data which can be processed by computer, and recognize the image with decision function. However, in actual applications, incomplete 3D images will be encountered. In order to screen the required image information from a large amount of images, it is necessary to recognize and match the image, and so the research has long-term application value. In this paper, sift algorithm was used to extract the feature vectors for incomplete 3D information recognition. Then, the modeling method of circular matching pattern was proposed, and the pattern of mathematical recognition was adopted in the process of image recognition. After that, on the basis of a large number of domestic and foreign research literatures, the process of "image hypothesis" converted to "image recognition" was completed. Finally, the system simulation was carried out by using Microsoft Visual Studio. For the incomplete 3D information image, the image feature recognition system was completed.

关键词： sift algorithm Image recognition Incomplete 3D information Wireless network

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FPGA Based Skin Disease Identification System Using sift algorithm and K-NN 12

FPGA Based Skin Disease Identification System Using Sift Alg...

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12th International Conference on Digital Image Processing (ICDIP)

作者： Mendoza, Joshua D. B. Linsangan, Noel B. Torres, Jumelyn L. Villanueva, Emmanuel Luis D. Mapua Univ Sch Elect Elect & Comp Engn Muralla St Manila 1002 Philippines

ISBN: (纸本)9781510638464

The initial assessment of any skin disease is usually made by visual inspection of doctors and skin specialists. Further tests may be recommended such as biopsy and pathological examination for a more accurate diagnosis. With the use of skin disease identification system, the diagnosis of infected skin is readily attainable without undergoing biopsy and pathological examination. The infected skin disease image is identified using sift algorithms with local features and K-NN classifier. The skin disease that will be identified are acne, psoriasis, eczema, rashes, hives, warts, tinea versicolor (an-an) and unknown skin disease. The system was confirmed to be efficient in identifying the aforementioned skin diseases. Identification of infected skin images is accomplished by K-Nearest Neighbors (K-NN) algorithm which shows an accuracy of 90% in functionality testing.

关键词： Biopsy sift algorithm K-Nearest Neighbor (K-NN) local features skin disease identification pathological visual inspection specialists

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Face Liveness Detection Using Eulerian Video Magnification and sift algorithm

Face Liveness Detection Using Eulerian Video Magnification a...

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IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS)

作者： Zhao, Wei Ma, Yan He, Xiaofu Huang, Hui Lin, Xiao Zhang, Yuping Shanghai Normal Univ Coll Informat Mech & Elect Engn Shanghai Peoples R China Columbia Univ Coll Phys & Surg New York NY USA

ISBN: (纸本)9781728165905

In this paper, face liveness detection method which is based on very short video is proposed. Firstly, spatial and temporal video processing is performed by using Eulerian video magnification. Next, the matching pairs between frames are extracted from the original video. Then, the paper constructs the feature histogram from the color difference between two pixels according to sift matching pairs. Finally, we use SVM classifier to determine the liveness of the subject. The experimental results show that the detection accuracy is 95% and the liveness detection can be completed in less than one second without any specific user action.

关键词： liveness detection video magnification sift algorithm feature histogram SVM

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Overview of Image Mosaic Technology based on sift algorithm

International Core Journal of Engineering

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International Core Journal of Engineering 2021年第8期7卷 499-507页

作者： Jinsong Zhang Lei Tang Zhiyao Sun Jun Liao

Image mosaic technology has developed rapidly in recent years. The core of image mosaic is the processing method of image registration. sift algorithm has become a common method of image registration because of its simple and accurate characteristics. This paper reviews a large number of literatures and summarizes the general process of sift algorithm, which includes scale space construction, key point detection and elimination, key point direction assignment, key point description and key point matching. After these processing, the target image can be fused and reconstructed into a new image with a wide view angle and more information.

关键词： Image Mosaic Image Registration sift algorithm Feature Extraction

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RESEARCH ON UAV IMAGE REGISTRATION BASED ON sift algorithm ACCELERATION 39

RESEARCH ON UAV IMAGE REGISTRATION BASED ON SIFT ALGORITHM A...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Li, Wei Li, Changhui Wang, Feng Guangzhou Urban Planning & Design Survey Res Inst Guangzhou 510060 Peoples R China

ISBN: (纸本)9781538691540

Considering the low real-time performance and the large amount of false matches exist in the feature matching stage of traditional Scale Invariant Feature Transform(sift) algorithm in unmanned aerial vehicle (UAV) remote sensing image registration. In this paper, a series of optimization methods for traditional sift algorithms are proposed, including sift execution process optimization, changing the parameters of scale space construction, Simplified method for judging the construction area of feature descriptor and construction of bidirectional matching filters. Experiments on UAV remote sensing images show that the optimization method can significantly improve the matching efficiency compared with traditional methods, and the comprehensive acceleration ratio is about 35% to 40%, which proves the effectiveness of the acceleration method.

关键词： sift algorithm UAV image feature matching Bidirectional Matching

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Target Recognition Based on sift algorithm for a Train Uncoupling Robot 31

Target Recognition Based on SIFT Algorithm for a Train Uncou...

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31st Chinese Control And Decision Conference (CCDC)

作者： Wang Jiaqi Wang Fangyong Yao Jianjun Zhao Yue Liu Ning Harbin Engn Univ Coll Mech & Elect Engn Harbin 150001 Peoples R China Northeast Forestry Univ Coll Engn & Technol Harbin 150001 Peoples R China

ISBN: (纸本)9781728101057

The train uncoupling robot is a 4-DOF robot which can complete the uncoupling work efficiently and accurately in the process of disassembly or marshalling of freight trains or passenger trains without the help of workers. The uncoupling work should be completed when the train and the uncoupling robot are both in motion. However, this increases the difficulty of recognizing the hook of trains and finishing the uncoupling work automatically. Therefore, the visual system of the robot plays a vital role during the uncoupling process so that it can be able to recognize the target hook by analyzing images and data from cameras and sensors. Furthermore, it should also have the ability to predict the motion planning of the object. In this paper, a visual control scheme is developed by using the Scale-invariant Feature Transform (sift) algorithm to recognize the hook of train in motion. It searches the extreme points as the key-points, and extracts the features such as position, scale and direction to match between the two images. The results indicate that the target hook can be recognized accurately and the recognition speed can meet the working requirements of the system by using the proposed visual control scheme even if the size of the target is varying or the target rotates moderately.

关键词： Train Uncoupling Robot Target Recognition sift algorithm Feature Descriptor

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Coin Recognition Method based on sift algorithm 4

Coin Recognition Method based on SIFT Algorithm

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4th International Conference on Information Science and Control Engineering (ICISCE)

作者： Xu, Jing Yang, Gongliu Liu, Yuanyuan Zhong, Jingjia Beihang Univ Sch Instrumentat Sci & Optoelect Engn Beijing 100191 Peoples R China Bejing Aerosp Times Opt Elect Technol Co Ltd Beijing 100854 Peoples R China

ISBN: (纸本)9781538630136

Coin recognition is one of the prime important activities for modern banking and currency processing systems in which machine vision is widely used. The technique at the heart of such systems is object recognition in a digital image. Although it has high recognition speed, the traditional method of coin recognition can not recognize the coins with similar sizes. This paper presents a method based on sift(scale invariant feature transform) algorithm for coin recognition. sift algorithm can handle the issues of rotations, scaling and illumination in a digital image. Therefore it can solve the problem about distinguishing the coins which have approximate size. In experiments, we compare the performances of Chinese coin recognition with our proposed method and the traditional method(based on size). The results demonstrate the feasibility and effectiveness of our approach.

关键词： coin recognition machine vision sift algorithm

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Image Registration Method Based on Improved sift algorithm and Essential Matrix Estimation

Image Registration Method Based on Improved SIFT Algorithm a...

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IEEE International Conference on Information and Automation (ICIA)

作者： Guo, Xiangkun Yang, Jing Lin, Hu Univ Chinese Acad Sci Beijing Peoples R China Chinese Acad Sci Shenyang Inst Comp Technol Shenyang Liaoning Peoples R China

ISBN: (纸本)9781538631546

In this paper, we propose an image registration algorithm based on improved sift (Scale-Invariant Feature Transform) algorithm and essential matrix estimation based on RANSAC (Random Sample Consensus) and AC-RANSAC (A Contrario RANSAC) algorithm. So that in the 3D reconstruction, we can directly restore the parameters of the camera by using the essential matrix model estimated by image registration algorithm. The essential matrix is a 5-parameter model, reflecting the relationship between the representation of the spatial image points in the camera coordinate system under different viewing angles. sift algorithm not only maintains the invariance of scale, rotation, brightness and so on, but also maintains a certain degree of stability to the angle change, affine transformation and noise, but the time performance is low and the matching accuracy is not high enough. Therefore, we propose to narrow the dimension of the sift feature vector to reduce the time consumption, and increase the similarity measure of the nearest neighbor distance less than 0.3 to calculate the feature point correspondence between images. The experimental results have demonstrated that our method not only can guarantee better time performance, but also can effectively eliminate the wrong match point, greatly improving the matching accuracy.

关键词： Image registration Essential matrix estimation sift algorithm AC-RANSAC algorithm

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Deep sea image mosaic based on sift algorithm 4

Deep sea image mosaic based on SIFT algorithm

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4th International Conference on Information Science and Control Engineering (ICISCE)

作者： Gang, Tong Huan, Liu Qingdao Univ Sci & Technol Sch Informat Sci & Technol Qingdao Peoples R China

ISBN: (纸本)9781538630136

This paper presents a new technique of deep sea image mosaic based on sift(Scale-invariant feature transform) algorithm. The sift algorithm by means of the median filter to the noise processing and itself has a good ability to resist scale changes, It can effectively match the characteristics of the two deep-sea biological images in the case of parallax. In the same coordinate system, the corresponding coordinate transformation is made according to the matching characteristic points. And the neighborhood average algorithm is used to optimize the processing. The whole process of using MATLAB to achieve, The program interface is simplified to enter two images.

关键词： sift algorithm image mosaic deep-sea images image registration

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