Binary Large Object-Based Approach for QR Code Detection in Uncontrolled Environments
Joint Authors
Lopez-Rincon, Omar
Starostenko, Oleg
Alarcon-Aquino, Vicente
Galan-Hernandez, Juan C.
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-07-26
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Information Technology and Computer Science
Abstract EN
Quick Response QR barcode detection in nonarbitrary environment is still a challenging task despite many existing applications for finding 2D symbols.
The main disadvantage of recent applications for QR code detection is a low performance for rotated and distorted single or multiple symbols in images with variable illumination and presence of noise.
In this paper, a particular solution for QR code detection in uncontrolled environments is presented.
The proposal consists in recognizing geometrical features of QR code using a binary large object- (BLOB-) based algorithm with subsequent iterative filtering QR symbol position detection patterns that do not require complex processing and training of classifiers frequently used for these purposes.
The high precision and speed are achieved by adaptive threshold binarization of integral images.
In contrast to well-known scanners, which fail to detect QR code with medium to strong blurring, significant nonuniform illumination, considerable symbol deformations, and noising, the proposed technique provides high recognition rate of 80%–100% with a speed compatible to real-time applications.
In particular, speed varies from 200 ms to 800 ms per single or multiple QR code detected simultaneously in images with resolution from 640 × 480 to 4080 × 2720, respectively.
American Psychological Association (APA)
Lopez-Rincon, Omar& Starostenko, Oleg& Alarcon-Aquino, Vicente& Galan-Hernandez, Juan C.. 2017. Binary Large Object-Based Approach for QR Code Detection in Uncontrolled Environments. Journal of Electrical and Computer Engineering،Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1175281
Modern Language Association (MLA)
Lopez-Rincon, Omar…[et al.]. Binary Large Object-Based Approach for QR Code Detection in Uncontrolled Environments. Journal of Electrical and Computer Engineering No. 2017 (2017), pp.1-15.
https://search.emarefa.net/detail/BIM-1175281
American Medical Association (AMA)
Lopez-Rincon, Omar& Starostenko, Oleg& Alarcon-Aquino, Vicente& Galan-Hernandez, Juan C.. Binary Large Object-Based Approach for QR Code Detection in Uncontrolled Environments. Journal of Electrical and Computer Engineering. 2017. Vol. 2017, no. 2017, pp.1-15.
https://search.emarefa.net/detail/BIM-1175281
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175281