Fast approach for QR code localization on images using Viola-Jones method

Sergey A. Usilin; Pavel V. Bezmaternykh; Vladimir V. Arlazarov

doi:10.1117/12.2559386

31 January 2020 Fast approach for QR code localization on images using Viola-Jones method

Sergey A. Usilin, Pavel V. Bezmaternykh, Vladimir V. Arlazarov

Proceedings Volume 11433, Twelfth International Conference on Machine Vision (ICMV 2019); 114333G (2020) https://doi.org/10.1117/12.2559386
Event: Twelfth International Conference on Machine Vision, 2019, Amsterdam, Netherlands

Abstract

In this paper, a method for QR Code localization on images obtained under uncontrolled environment is presented. The proposed method is a modified Viola-Jones object detection method in which features are calculated over the directional edge image, and a tree classifier is used instead of cascade classifier. The experiments show that the use of the QR Code localization method described in the paper can significantly improve the quality of the existing decoding algorithms. The high performance of the developed method makes it possible to use it in various real-time recognition systems.

Citation Download Citation

Sergey A. Usilin, Pavel V. Bezmaternykh, and Vladimir V. Arlazarov "Fast approach for QR code localization on images using Viola-Jones method", Proc. SPIE 11433, Twelfth International Conference on Machine Vision (ICMV 2019), 114333G (31 January 2020); https://doi.org/10.1117/12.2559386

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

Includes PDF, HTML & Video, when available