Image stitching
This report describes how SIFT keypoints are obtained by using Difference-of-Gaussian for detecting local maxima and minima and methods to filter detected local features in order to obtain stable keypoints. The magnitudes of gradient and orientations are added to each keypoint before creating each k...
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Main Author: | |
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Format: | Final Year Project |
Language: | English |
Published: |
2011
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Subjects: | |
Online Access: | http://hdl.handle.net/10356/46173 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | This report describes how SIFT keypoints are obtained by using Difference-of-Gaussian for detecting local maxima and minima and methods to filter detected local features in order to obtain stable keypoints. The magnitudes of gradient and orientations are added to each keypoint before creating each keypoint descriptor.These correspondences are then used to find m candidate matching images for each image. Based on the extracted local features, image transformation matrices are built, images are to be processed based on the transformation matrices. This report also discussed methods for blending images to create seamless panorama in C++. |
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