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Binarization of Matrix Codes

  • Sven Behnke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2766)

Abstract

In this chapter, the binarization of matrix codes is investigated as an application of supervised learning of image processing tasks using a recurrent version of the Neural Abstraction Pyramid.

The desired network output is computed using an adaptive thresholding method for images of high contrast. The network is trained to iteratively produce it even when the contrast is lowered and typical noise is added to the input.

Keywords

Original Image Recognition Error Adaptive Thresholding Matrix Code Degraded Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Sven Behnke

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