Research on snowpeach image matching based on improved SIFT algorithm

Lei Zheng

doi:10.1117/12.3034932

11 July 2024 Research on snowpeach image matching based on improved SIFT algorithm

Lei Zheng

Author Affiliations +

Proceedings Volume 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024); 132101A (2024) https://doi.org/10.1117/12.3034932
Event: Third International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2024, Wuhan, China

Abstract

Based on the product tracing and quality monitoring requirements of Lijiang snowpeach, a solution using image matching for product identification was proposed. In response to the slow speed and false matching problems of traditional SIFT algorithm in snowpeach image matching, an improved SIFT algorithm was proposed, which uses Laplace algorithm for image enhancement, extracts more image information, adopts fixed-position feature vector extraction method, reduces the feature vector of image keypoints from 128 dimensions to 64 dimensions, and uses center-distance method to remove edge keypoints, reduces wrong matches. Experimental results indicate that the algorithm effectively improves the speed and accuracy of image matching.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Lei Zheng "Research on snowpeach image matching based on improved SIFT algorithm", Proc. SPIE 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024), 132101A (11 July 2024); https://doi.org/10.1117/12.3034932

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE