ChainLineNet: Deep-Learning-Based Segmentation and Parameterization of Chain Lines in Historical Prints

ChainLineNet: Deep-Learning-Based Segmentation and Parameterization of Chain Lines in Historical Prints

The paper structure of historical prints is sort of a unique fingerprint. Paper with the same origin shows similar chain line distances. As the manual measurement of chain line distances is time consuming, the automatic detection of chain lines is beneficial. We propose an end-to-end trainable deep...

Full description

Bibliographic Details
Main Authors: Aline Sindel, Thomas Klinke, Andreas Maier, Vincent Christlein
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Journal of Imaging
Subjects:
line segmentation
line detection
line parameterization
generative adversarial networks
Fourier transform
differentiable line fitting
Online Access:https://www.mdpi.com/2313-433X/7/7/120

Internet

https://www.mdpi.com/2313-433X/7/7/120

Similar Items