TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Experimental Optimal Choice Of Initial Candidate Inliers Of The Feature Pairs With Well-Ordering Property For The Sample Consensus Method In The Stitching Of Drone-based Aerial Images |
| 영문제목(English Title) |
Experimental Optimal Choice Of Initial Candidate Inliers Of The Feature Pairs With Well-Ordering Property For The Sample Consensus Method In The Stitching Of Drone-based Aerial Images |
| 저자(Author) |
Byeong-Chun Shin
Jeong-Kweon Seo
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| 원문수록처(Citation) |
VOL 14 NO. 04 PP. 1648 ~ 1672 (2020. 04) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
There are several types of image registration in the sense of stitching separated images that overlap each other. One of these is feature-based registration by a common feature descriptor. In this study, we generate a mosaic of images using feature-based registration for drone aerial images. As a feature descriptor, we apply the scale-invariant feature transform descriptor. In order to investigate the authenticity of the feature points and to have the mapping function, we employ the sample consensus method; we consider the sensed image’s inherent characteristic such as the geometric congruence between the feature points of the images to propose a novel hypothesis estimation of the mapping function of the stitching via some optimally chosen initial candidate inliers in the sample consensus method. Based on the experimental results, we show the efficiency of the proposed method compared with benchmark methodologies of random sampling consensus method (RANSAC); the well-ordering property defined in the context and the extensive stitching examples have supported the utility. Moreover, the sample consensus scheme proposed in this study is uncomplicated and robust, and some fatal miss stitching by RANSAC is remarkably reduced in the measure of the pixel difference.
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| 키워드(Keyword) |
Scale-invariant feature transform
Computer Algorithms
Feature matching
Stitching images
Drone-based aerial image
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| 파일첨부 |
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