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QR Code Localization Using Boosted Cascade of Weak Classifiers

  • Péter Bodnár
  • László G. Nyúl
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8814)

Abstract

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 steps: 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.

Keywords

QR code Object detection Cascade classifier HAAR LBP HOG 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Image Processing and Computer GraphicsUniversity of SzegedSzegedHungary

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