Open AccessRecognition of distorted QR codes with one missing position detection pattern
Author(s) -
Huang Jianfen,
Li Liyan,
Wang Xiao,
Lu Baoli,
Liu Yuliang
Publication year - 2020
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2019.1095
Subject(s) - decoding methods , code (set theory) , computer science , position (finance) , algorithm , range (aeronautics) , artificial intelligence , pattern recognition (psychology) , computer vision , engineering , set (abstract data type) , finance , economics , programming language , aerospace engineering
Quick response (QR) codes are widely used in many fields. Various QR code recognition approaches have been proposed to improve the accuracy of decoding QR code. However, the recognition of distorted QR codes with one missing position detection pattern (PDP) remains a problem. In this study, based on the vector relationship and the structural features, the authors introduce a new method for decoding distorted QR code with one missing PDP. Three methods, Zxing, Halcon, and the newly proposed method, are used to test the decoding capability. For QR codes with one missing PDP, the experimental results show that the proposed method could meet the recognition angle range as much as 110°, while Zxing fails to recognise, and the angle of decoding for Halcon is 90°. Especially, the proposed method is available at an extremely harsh luminance and contrast environment, e.g. both phases as a 60% discount, when the decoding angle of Halcon is only 35°, while the proposed one better than 2.7 times of it. Besides, the proposed method is more robust to decode the QR codes with a missing PDP under different backgrounds and noisy images.