Open AccessOptimization and Innovation of SIFT Feature Matching Algorithm in Static Image Stitching Scheme
Author(s) -
Yuan Jiao
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1881/3/032017
Subject(s) - image stitching , scale invariant feature transform , artificial intelligence , computer vision , computer science , feature detection (computer vision) , image registration , feature extraction , feature (linguistics) , robustness (evolution) , pattern recognition (psychology) , image fusion , image processing , image (mathematics) , linguistics , philosophy , biochemistry , chemistry , gene
With the development of computer technology, people can obtain electronic images by a variety of means, but these images often need to obtain a panoramic view of a large field of view from multiple limited field of view images because the field of view is smaller than that of humans, and image stitching technology can be very good Solve the contradiction between vision and resolution. This paper studies the extraction and registration of image feature points and its related technologies, including image feature detection and extraction, point feature-based matching, and image fusion. According to the requirements of matching and image splicing, the feature points with good robustness to image deformation and occlusion are used as image features to indicate that it meets the requirements of image splicing registration. This paper studies and designs an improved algorithm to improve the accuracy of feature points extraction. Further research and analysis of the SIFT operator based on the characteristics of the invariant technology realize that the feature points extracted from the image can be used for reliable matching of an object or scene from different perspectives.