Advertisement
Published in:
2015 | OriginalPaper | Chapter
Insights on the Use of Convolutional Neural Networks for Document Image Binarization
Authors : J. Pastor-Pellicer, S. España-Boquera, F. Zamora-Martínez, M. Zeshan Afzal, Maria Jose Castro-Bleda
Published in: Advances in Computational Intelligence
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Convolutional Neural Networks have systematically shown good performance in Computer Vision and in Handwritten Text Recognition tasks. This paper proposes the use of these models for document image binarization. The main idea is to classify each pixel of the image into foreground and background from a sliding window centered at the pixel to be classified. An experimental analysis on the effect of sensitive parameters and some working topologies are proposed using two different corpora, of very different properties: DIBCO and Santgall.