A Neural Network for Grey Level and Color Correction used in Photo nishing

Abstract

The application of a multi-layer perceptron for color and gray level correction in the eld of photoonishing is presented. It is shown, that a neural network 1] can improve the overall performance of a state of the art photo printer. The improved correction ability will reduce the number of unsalable pictures and thus lowers the production costs for the photo laboratory. The training experiments were carried out on a database of 30,000 photos using the MUSIC parallel supercomputer. The MUSIC system made it possible, for the rst time, to process this large database in a reasonable time.

1 Figure or Table

Cite this paper

@inproceedings{Kocheisen1996ANN, title={A Neural Network for Grey Level and Color Correction used in Photo nishing}, author={Michael Kocheisen and Gerhard Troster}, year={1996} }