CNN model for identifying colors under different illumination conditions via land's experiments

Akos Zarandy, Edward Grawes, Tamas Roska, Frank Werblin, Leon O. Chua

Research output: Contribution to conferencePaper

Abstract

In this paper we present a CNN model for separating colors under different illumination conditions. The color model is based on Land's assumption: the individual monochromatic channels are processed separately. However we use a different channel processing model. The model was evaluated on a Mondrian image.

Original languageEnglish
Pages163-168
Number of pages6
Publication statusPublished - Dec 1 1996
EventProceedings of the 1996 4th IEEE International Workshop on Cellular Neural Networks, and Their Applications, CNNA-96 - Seville, Spain
Duration: Jun 24 1996Jun 26 1996

Other

OtherProceedings of the 1996 4th IEEE International Workshop on Cellular Neural Networks, and Their Applications, CNNA-96
CitySeville, Spain
Period6/24/966/26/96

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ASJC Scopus subject areas

  • Software

Cite this

Zarandy, A., Grawes, E., Roska, T., Werblin, F., & Chua, L. O. (1996). CNN model for identifying colors under different illumination conditions via land's experiments. 163-168. Paper presented at Proceedings of the 1996 4th IEEE International Workshop on Cellular Neural Networks, and Their Applications, CNNA-96, Seville, Spain, .