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Color Reduction Using Local Features and a Kohonen Self-organized Feature Map Neural Network by Nikos Papamarkos is a Computer Science article available to read on EtoBox.

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This paper proposes a new method for reducing the number of colors in an image. The proposed approach uses both the image color components and local image characteristics to feed a Kohonen self-organized feature map (SOFM) neural network. After training, the neurons of the output competition layer define the proper color classes. The final image has the dominant image colors and its texture approaches the image local characteristics used. To speed up the entire algorithm and reduce memory requirements, a fractal scanning subsampling technique can be used. The method is applicable to all types of color images and can be easily extended to accommodate any type of spatial characteristics. Several experimental and comparative results are presented.

Who reads Color Reduction Using Local Features and a Kohonen Self-organized Feature Map Neural Network?

Author

Nikos Papamarkos

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Inc.; Wiley (ISSN 0899-9457)

Published

1999

Language

EN

Field

Computer Science (Physical Sciences)