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

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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Determiningrelativeposition and attitude of a close non-cooperative target based on the sift algorithm

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Journal of Beijing Institute of Technology 2014年第3期23卷 390-394页

作者：郝伟伟张晓芳黄宇杨峰郭百巍 School of Optoelectronics Beijing Institute of Technology School of Aerospace Engineering Beijing Institute of Technology

A binocular stereo vision positioning method based on the scale-invariant feature trans- form （sift） algorithm is proposed. The sift algorithm is for extracting distinctive invariant features from images. First, image median filtering is used to eliminate image noise. Then, according to the characteristics of the target satellite, image map is used to extract the middle part of the target satel- lite. At last, the feature match point under the sift algorithm is extracted, and the three-dimension- al position and orientation are calculated. The features are invariant to image scale and rotation, and are shown to provide robust matching across a substantial range of affine distortion, change in 3D viewpoint, addition of noise, and change in illumination. The experimental result shows that the al- gorithm works well and the maximum relative error is within 0. 02 m and 2.5 o

关键词： binocular stereo vision image matching sift algorithm pose measurement

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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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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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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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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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Research on the sift algorithm in Image Matching

Research on the SIFT Algorithm in Image Matching

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2nd International Conference on Frontiers of Manufacturing and Design Science (ICFMD 2011)

作者： Cong, Yuan Chen, Xiaorong Li, Yiting Shanghai Univ Sci & Technol Shanghai 200093 Peoples R China Infinite Shanghai Commun Terminals Ltd Shanghai Peoples R China

ISBN: (纸本)9783037852828

sift feature matching algorithm is hot in the field of the currently feature matching research, its matching with the strong ability can deal with the translation, rotation, affine transformation occurring between images, and it also have a stable image feature matching ability to the images filmed at any angle. sift algorithm is adopted in this paper, matching feature point through the scale space, calculating the histogram of detecting feature point neighborhood of gradient direction characteristic vector and generation to sift eigenvector and the key points similarity measure. From different setting threshold, scale scaling, rotating, noise on the experiment, the experiment result proves this algorithm in the above aspects has good robustness, suitable for mass characteristic database of rapid, accurate matching.

关键词： Image Matching sift algorithm feature vector scale space

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Application of sift algorithm in 3D Scene Reconstruction

Application of SIFT Algorithm in 3D Scene Reconstruction

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2nd International Conference on Energy, Environment and Sustainable Development (EESD 2012)

作者： Zhang, Baofeng Li, Jialu Zhang, Xiaoling Tianjin Univ Technol Tianjin Key Lab Control Theory & Applicat Complic Tianjin 300384 Peoples R China

ISBN: (纸本)9783037855522

Applying sift algorithm in 3D scene reconstruction can improve the system accuracy. Firstly, the paper analysed the characteristics of sift algorithm. Then 3D scene reconstruction process was introduced briefly. At last, the experimental images were matched by sift algorithm, and a suggestion value bound was given by comparing the matching result of different nearest ratio. The experimental results show that matching by sift algorithm has excellent accuracy, and it can be further applied to the 3D scene reconstruction system.

关键词： sift algorithm stereo matching 3D scene reconstruction

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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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