Image jigsaw puzzle
This paper presents the process of multiple image stitching. Using a robust feature-base matching method to detect and extract distinctive invariant features from image. Applying fitting model to remove noisy point and outliers to enhance feature matching result. Estimating and optimizing the camera...
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Nanyang Technological University
2020
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Online Access: | https://hdl.handle.net/10356/138955 |
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sg-ntu-dr.10356-1389552023-07-07T18:38:37Z Image jigsaw puzzle Lin, HaoXian Chua Chin Seng School of Electrical and Electronic Engineering ecschua@ntu.edu.sg Engineering::Electrical and electronic engineering This paper presents the process of multiple image stitching. Using a robust feature-base matching method to detect and extract distinctive invariant features from image. Applying fitting model to remove noisy point and outliers to enhance feature matching result. Estimating and optimizing the camera parameters for correct image transformation. Finally, correct any distortion in the panorama to restore the naturality. Bachelor of Engineering (Electrical and Electronic Engineering) 2020-05-14T05:38:22Z 2020-05-14T05:38:22Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/138955 en A1046-191 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Lin, HaoXian Image jigsaw puzzle |
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This paper presents the process of multiple image stitching. Using a robust feature-base matching method to detect and extract distinctive invariant features from image. Applying fitting model to remove noisy point and outliers to enhance feature matching result. Estimating and optimizing the camera parameters for correct image transformation. Finally, correct any distortion in the panorama to restore the naturality. |
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Chua Chin Seng |
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Chua Chin Seng Lin, HaoXian |
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Final Year Project |
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Lin, HaoXian |
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Lin, HaoXian |
title |
Image jigsaw puzzle |
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Image jigsaw puzzle |
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Image jigsaw puzzle |
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Image jigsaw puzzle |
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Image jigsaw puzzle |
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image jigsaw puzzle |
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Nanyang Technological University |
publishDate |
2020 |
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https://hdl.handle.net/10356/138955 |
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1772828884330348544 |