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检索条件"主题词=Sift Algorithm"

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Design and implementation of multi-billionpixel imaging system 34

Design and implementation of multi-billionpixel imaging syst...

引用

34th Chinese Control and Decision Conference (CCDC)

作者： Yin Zihang Zhu Yueming Deng Huiping Wuhan Univ Sci & Technol Sch Informat Sci & Engn Wuhan 430081 Peoples R China

ISBN: (纸本)9781665478960

Aiming at the high cost and complex imaging system faced by current billion-pixel imaging systems, a low-cost and easy-to-use billion-pixel imaging system based on sift algorithm is proposed. The system first uses Zhang Zhengyou's camera calibration method to calculate the camera's internal and external parameters and distortion coefficients, and geometrically corrects the image;then uses the sift algorithm to match the same feature points of the same group of photos, and further uses image stitching to image the image based on the extracted feature points Carry out stitching, and finally apply the beam adjustment method to smoothly optimize the stitched image and eliminate the re-projection error;the imaging effect of hundreds of millions of pixels is realized.

关键词： Zhang Zhengyou camera calibration sift algorithm Image stitching Bundle adjustment

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Automatic registration of multi-view 3D laser point cloud based on Image Registration and Ameliorated ICP algorithm

Automatic registration of multi-view 3D laser point cloud ba...

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International Symposium on Photoelectronic Detection and Imaging 2011 - Laser Sensing and Imaging and Biological and Medical Applications of Photonics Sensing and Imaging

作者： Zhao Ziming Hao Xiangyang Zhao Song Su Yintai Informat Engn Univ Inst Surveying & Mapping Zhengzhou 450052 Peoples R China

ISBN: (纸本)9780819488336

In the process of the registration of multi-view point cloud, it's difficult to extract the feature points at present. In view of this condition, the article advances a new automatic registration method of multi-view point cloud based on Image Registration and ICP algorithm. After the registration of point cloud and corresponding image, the feather can be extracted from the image that has plenty of textures compared with the point cloud. And it's beneficial to improve the precision and efficiency for the next registration. The experimental results demonstrate that the new method guarantees accurate fine registration.

关键词： 3D laser scanning Registration of multi-view 3D laser point cloud RANSAC sift algorithm Ameliorated ICP algorithm

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An IoT-Based Smart Shopping Cart Using the Contemporary Barcode Scanner 1

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Symposium-B on Intelligent Embedded Systems / 1st International Conference on NextGen Electronic Technologies - Silicon to Software (ICNETS2)

作者： Prithvish, V. N. Agrawal, Shraddha Alex, John Sahaya Rani VIT Univ Sch Elect Engn Chennai Campus Chennai Tamil Nadu India

ISBN: (数字)9789811085758

ISBN: (纸本)9789811085758;9789811085741

An efficacious prototyping of an intelligent Internet of Things (IoT)-based smart cart that primarily enhances the shopping experience of the customers as well as owners. The assembly of the smart cart consists of a contemporary barcode scanner from the present-day shopping scenario, feedback systems providing product weight and product imaging to avoid discrepancies, a cloud-based database and an embedded hardware to connect the above. The mechanism facilitates the customer to add and remove products throughout the shopping, updating the bill instantaneously, and further reflecting changes in the inventory. The framework incorporates a Parse cloud-based inventory to ease the managerial task at the owner end. Further focus has been also given on the proper placement of all the components on a cart for the efficient working of the shop, keeping user's ease of usage in mind.

关键词： Smart cart IoT Pars Beagle Bone Black TVS electronics BSC-101 star RTL-8188EU sift algorithm Load cell Barcode scanner

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The Research on and Application of Detecting Technology in Car Intelligent Video-aided Driving System

The Research on and Application of Detecting Technology in C...

引用

International Symposium on Photoelectronic Detection and Imaging 2011 - Advances in Imaging Detectors and Applications

作者： Chen Yuelin Sun Liangbo Lu Chong Guilin Univ Elect Technol Dept Technol & Informat Guilin 541004 Peoples R China Guilin Univ Elect Technol Coll Appl Sci & Technol Guiyang 541004 Peoples R China

ISBN: (纸本)9780819488350

Analyze the advantages and disadvantages and applying condition of the existing object detecting algorithm, aims to body's variation and real-time and dynamic, combing with Histogram of Gradient statistic method, classify organ of level-connect mechanism and leaning algorithm based on Adaboost of face-detecting Boosted Cascad algorithm, to realize the object detect in car aided driving system. References the sift algorithm rationale and algorithm tracing steability to match and trace the object by characteristic in local area, eliminate the unuse information, simple the search area and speed the tracing. By practical video testing, this method does well in passengers and cars real-time detecting and tracing.

关键词： Boosted Casca algorithm Histogram of Gradient statistic Support Vector Machine sift algorithm object detection and tracking

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Image-based Automatic Recognition of Larvae

Image-based Automatic Recognition of Larvae

引用

6th International Symposium on Precision Engineering Measurements and Instrumentation

作者： Sang, Ru Yu, Guiying Fan, Weijun Guo, Tiantai China Jiliang Univ Coll Metrol & Measurement Engn Hangzhou 310018 Peoples R China

ISBN: (纸本)9780819479402

As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (sift) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.

关键词： Larvae recognition Image processing Color segmentation sift algorithm

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Augmented Reality Registration Method Based on Natural Feature Points 17

Augmented Reality Registration Method Based on Natural Featu...

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IEEE 17th International Conference on Communication Technology (ICCT)

作者： Li, Qianyu Li, Yingxiang Tian, Juan Ren, Dehao Chengdu Univ Informat Technol Cehngdu Peoples R China

ISBN: (纸本)9781509039449

A three-dimensional registration method based on natural feature points is presented, which is applied to the augmented reality system. Firstly, several common feature extraction algorithms have been compared in this paper, and the sift algorithm is applied to improve the matching accuracy as a descriptor matching method. And then the data of ten key image frames is used to reconstruct the 3D structure of the scene. When the real-time image data is input, the key frame which mostly matches the current image is selected, and the image matching method based on key frame is used to obtain the camera pose. Finally, improved Lucas-Kanade method for real-time tracking is adopted, not only maintaining the accuracy of registration but reducing the system computing time. The experimental results shown that the method achieves a effect of real-time tracking and accurate registration, and can keep a better registration precision.

关键词： three-dimensional registration natural feature points sift algorithm augmented reality

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Design and realization of an Image mosaic system on the CCD aerial camera

Design and realization of an Image mosaic system on the CCD ...

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International Conference on Optical Instruments and Technology - Optoelectronic Imaging and Processing Technology

作者： Liu Hai ying Wang Peng Zhu Hai bin Li Yan Zhang Shao jun 228 Plant China North Ind Grp Corp Changchun 130103 Peoples R China Tsinghua Univ Dept Precis Instruments & Mechanol Beijing 100084 Peoples R China TML Agr Stn Jiutai Jiutai 130117 Jilin Peoples R China

ISBN: (纸本)9781628418033

It has long been difficulties in aerial photograph to stitch multi-route images into a panoramic image in real time for multi-route flight framing CCD camera with very large amount of data, and high accuracy requirements. An automatic aerial image mosaic system based on GPU development platform is described in this paper. Parallel computing of sift feature extraction and matching algorithm module is achieved by using CUDA technology for motion model parameter estimation on the platform, which makes it's possible to stitch multiple CCD images in real-time. Aerial tests proved that the mosaic system meets the user's requirements with 99% accuracy and 30 to 50 times' speed improvement of the normal mosaic system.

关键词： CCD aerial camera stitch in real-time CUDA technology GPU sift algorithm

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Research on Improved Image Registration algorithm Based on PROSAC algorithm 11

Research on Improved Image Registration Algorithm Based on P...

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11th International Conference on Digital Image Processing (ICDIP)

作者： Li, Xiangyu Lei, Tianjie Zhao, Chun Huang, Jintao Yuan, Man Wang, Jiabao China Inst Water Resources & Hydropower Res IWHR Beijing 100038 Peoples R China North China Univ Water Resources & Elect Power NC Zhengzhou 450000 Peoples R China

ISBN: (数字)9781510630765

ISBN: (纸本)9781510630765

In order to solve the problems of poor stability and multiple mismatching points in image registration, most scholars have used Random Sample Consensus (RANSAC) algorithm to optimize the matching algorithm. However, because of the randomness of the RANSAC algorithm itself, the matching algorithm has poor stability, low registration efficiency and poor robustness. To solve this problem, an improved sift (Scale-invariant feature transform) image registration optimization algorithm based on PROSAC (Progressive Sampling Consensus) was proposed. The experimental results showed that the proposed image registration optimization algorithm could effectively solve the problems of error matching and low efficiency in the process of image matching. Using the same image to test, the average correct registration rate of the traditional RANSAC improved sift algorithm was 82%, and the average running time was 36 seconds. The average correct registration rate of the sift image registration algorithm based on PROSAC improved sift image registration algorithm was 86.67%, the average running time was 26.51 seconds, and the running efficiency was increased by 36%. Therefore, the improved sift image registration algorithm based on PROSAC has higher robustness, can meet the needs of fast image mosaic, and has broad application prospects.

关键词： Image stitching sift algorithm RANSAC algorithm PROSAC algorithm

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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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Comparative analysis of interest points detection techniques for the registration of infrared and visible aerial photographs in pasture crops 42

Comparative analysis of interest points detection techniques...

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Conference on Applications of Digital Image Processing XLII

作者： Forero, Manuel G. Acosta, Andrea Ducuara, Alvaro Godoy, Yesmar Guillermo Moreno, Juan Univ Ibague Fac Ingn Ibague Colombia

ISBN: (数字)9781510629684

ISBN: (纸本)9781510629684

Registration is used in precision agriculture to adjust near-infrared aerial photographs and visible crop spectra to analyze crop growth and development. Vegetation indices can be calculated from the registered images. It is therefore necessary to study and analyze the most popular techniques for detecting points of interest. The points of interest found are used as reference in the images of both spectra. Thus, a comparative study of pasture crop images with four of the most popular point of interest detection techniques (Harris, sift, SURF and ORB) is presented here.

关键词： Interest points Harris Corners Detector sift algorithm sift Descriptor SURF Method ORB algorithm FAST Detector BRIEF Descriptor Multimodality Image Recording

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