Dissertation
Dissertation > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device

The Research and Application of the Unmanned Aerial Vehicle Image Matching Based on Feature Point

Author LiXianZuo
Tutor ZhangChunSen
School Xi'an University of Science and Technology
Course Cartography and Geographic Information Systems
Keywords Local invariant feature Image Matching colour-sift Large_SIFT UAV images
CLC TP391.41
Type Master's thesis
Year 2011
Downloads 248
Quotes 3
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Image matching technology is the core content of computer vision and digital image processing , is widely used in target recognition , 3D reconstruction , stereo matching , motion tracking , and other fields . UAV remote sensing system platform is not smooth , the camera attitude stability , these factors gave match brings difficulties , therefore , suitable for different degree of overlap , the big rotating angle images of the same name features automatic matching algorithm , is a low-altitude remote sensing image Can be applied to production practice premise . UAV remote sensing image target matching study and explore in-depth study of the matching algorithm based on feature points around the feature point extraction , based on the characteristics of the feature point description and feature matching three aspects of the research and experimentation . The article 's main research content and innovations are as follows : 1. Analysis of the importance of UAV remote sensing images and application status , summarizes the classification and study of the status quo of the image matching technique to analyze the main problems faced by the UAV remote sensing image matching technology . 2 . Study based on the local characteristics of the image gray information , respectively, from the rotational invariance , scale invariance , affine invariant introduced a variety of feature extraction operator conducted a comprehensive evaluation of the properties of each operator . Feature descriptor system research and analysis . Proposed three kinds of methods to remove false matches , respectively, based on the the RANSAC method the linear orthomorphisms transformation model , the correlation coefficient method and the main direction angle method , the effect of the three methods through experiments . Based on the color information of the image colour-SIFT feature matching algorithm , and to compare the effect of the SIFT algorithm , SURF algorithm and colour-SIFT algorithm for UAV image matching . The SIFT algorithm performance large format aerial imagery processing defects and deficiencies imaging the block Large_SIFT algorithm , the algorithm can be a good application in the UAV image matching process . 6 . Designed a set of the UAV images automatic aerial triangulation the measurement system GodWork, system of UAV remote sensing image matching part , used the previously mentioned large_sift algorithm , epipolar constraints , pyramid matching strategy . .

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