Image Stitching based on Feature Detection and Extraction: An Analysis

DOI

10.2991/978-94-6463-540-9_72How to use a DOI?

Keywords

Image Stitching; Features Detection; Features Extraction

Abstract

Image stitching is a popular research area in the fields of computer vision and computer graphics. The feature points of images provide crucial information for this process. The accurate extraction of these features is essential to minimize misalignment and defects in the final stitched image. This paper extensively discusses the application of deep neural network-based feature detection algorithms in image stitching. Initially, it introduces several commonly used feature detection algorithms such as scale invariant feature transform (SIFT), speed up robust feature (SURF), before delving into deep learning-based methods, specifically focusing on convolutional neural network-based feature detectors. The paper elaborates on the operational mechanisms of these algorithms in image stitching, emphasizing the efficient extraction of key feature points from images and the subsequent matching of these points for seamless stitching. Moreover, a comparative analysis of the advantages and limitations of these modern methods relative to conventional approaches is provided. The paper concludes with a concise overview of the current challenges encountered in the realm of image stitching, including issues related to feature extraction and matching in complex scenes, as well as performance and efficiency constraints when dealing with large-scale image datasets. In summary, the paper offers insights into the advancements in image stitching techniques and highlights potential areas for future research and development.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Nan Zhao
PY  - 2024
DA  - 2024/10/16
TI  - Image Stitching based on Feature Detection and Extraction: An Analysis
BT  - Proceedings of the 2024 2nd International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2024)
PB  - Atlantis Press
SP  - 704
EP  - 713
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-540-9_72
DO  - 10.2991/978-94-6463-540-9_72
ID  - Zhao2024
ER  -