Panoramic image stitching
A panoramic image can be formed by stitching together two images with overlapping scenes. The overlapping images taken usually have common points called interest points which can be extracted to stitch the two images together. The interest points can then be matched and merged to form the panoramic...
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sg-ntu-dr.10356-683152023-07-07T17:39:37Z Panoramic image stitching Muhammad Zukhairi Bin Ramli Chua Chin Seng School of Electrical and Electronic Engineering DRNTU::Engineering A panoramic image can be formed by stitching together two images with overlapping scenes. The overlapping images taken usually have common points called interest points which can be extracted to stitch the two images together. The interest points can then be matched and merged to form the panoramic image. [1] This report will describe how the interest points are located and extracted using Harris Corner Detector with the help of a 2-by-2 matrix and using eigenvalues to determine whether the points are suitable enough. Cross correlation will then be used to match the interest points from the two images together. RANSAC will then get rid of the outliers leaving only the inliers to blend the two images together. This report will discuss on how different scenarios will affect the resulted stitched image. Images that are rotated, scaled and also those with their illumination and perspective changed will be tested. Bachelor of Engineering 2016-05-25T06:23:58Z 2016-05-25T06:23:58Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/68315 en Nanyang Technological University 84 p. application/pdf |
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DRNTU::Engineering Muhammad Zukhairi Bin Ramli Panoramic image stitching |
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A panoramic image can be formed by stitching together two images with overlapping scenes. The overlapping images taken usually have common points called interest points which can be extracted to stitch the two images together. The interest points can then be matched and merged to form the panoramic image. [1]
This report will describe how the interest points are located and extracted using Harris Corner Detector with the help of a 2-by-2 matrix and using eigenvalues to determine whether the points are suitable enough. Cross correlation will then be used to match the interest points from the two images together. RANSAC will then get rid of the outliers leaving only the inliers to blend the two images together.
This report will discuss on how different scenarios will affect the resulted stitched image. Images that are rotated, scaled and also those with their illumination and perspective changed will be tested. |
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Chua Chin Seng |
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Chua Chin Seng Muhammad Zukhairi Bin Ramli |
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Final Year Project |
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Muhammad Zukhairi Bin Ramli |
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Muhammad Zukhairi Bin Ramli |
title |
Panoramic image stitching |
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Panoramic image stitching |
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Panoramic image stitching |
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Panoramic image stitching |
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Panoramic image stitching |
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panoramic image stitching |
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2016 |
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http://hdl.handle.net/10356/68315 |
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1772828758380642304 |