TY  - JOUR
PB  - Szegedi Tudományegyetem
N2  - Usage of computer-readable visual codes became common in our 
everyday life at industrial environments and private use. The 
reading process of visual codes consists of two tasks: 
localization and data decoding. Unsupervised localization is 
desirable at industrial setups and for visually impaired 
people. This paper examines localization efficiency of 
cascade classifiers using Haar-like features, Local Binary 
Patterns and Histograms of Oriented Gradients, trained for 
the finder patterns of QR codes and for the whole code region 
as well, and proposes improvements in post-processing.
ID  - publicatio8459
AV  - public
IS  - 1
Y1  - 2015///
TI  - Improved QR Code Localization Using Boosted Cascade of Weak Classifiers
JF  - Acta Cybernetica (Szeged)
A1  -  Bodnár Péter
A1  -  Nyúl László
UR  - http://www.inf.u-szeged.hu/actacybernetica/edb/vol22n1/pdf/Bodnar_2015_ActaCybernetica.pdf
SN  - 0324-721X
SP  - 21
EP  - 33
VL  - 22
N1  - FELTÖLT?: Nyúl László Gábor - nyul@inf.u-szeged.hu
ER  -