Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Chinese Optics Letters
  • Vol. 6,
  • Issue 3,
  • pp. 231-234
  • (2008)

Scanner color management model based on improved back-propagation neural network

Not Accessible

Your library or personal account may give you access

Abstract

Scanner color management is one of the key techniques for color reproduction in information optics. A new scanner color management model is presented based on analyzing rendering principle of scanning objects. In this model, a standard color target is taken as experimental sample. Color blocks in color shade area are used to substitute complete color space to solve the difficulties in selecting experimental color blocks. Immune genetic algorithm is used to correct back-propagation neural network (BPNN) to speed up the convergence of the model. Experimental results show that the model can improve the accuracy of scanner color management.

© 2008 Chinese Optics Letters

PDF Article
More Like This
Parameter optimization and real-time calibration of a measurement-device-independent quantum key distribution network based on a back propagation artificial neural network

Feng-Yu Lu, Zhen-Qiang Yin, Chao Wang, Chao-Han Cui, Jun Teng, Shuang Wang, Wei Chen, Wei Huang, Bing-Jie Xu, Guang-Can Guo, and Zheng-Fu Han
J. Opt. Soc. Am. B 36(3) B92-B98 (2019)

Object-based color constancy in a deep neural network

Hamed Heidari-Gorji and Karl R. Gegenfurtner
J. Opt. Soc. Am. A 40(3) A48-A56 (2023)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved