DocumentCode :
2749395
Title :
A neural network for grey level and color correction used in photofinishing
Author :
Kocheisen, Michael ; Müller, Urs A. ; Tröster, Gerhard
Author_Institution :
Electron. Lab., Swiss Federal Inst. of Technol., Zurich, Switzerland
Volume :
4
fYear :
1996
fDate :
3-6 Jun 1996
Firstpage :
2166
Abstract :
The application of a multilayer perceptron for color and gray level correction in the field of photofinishing is presented. It is shown, that a neural network 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 first time, to process this large database in a reasonable time
Keywords :
chemical technology; multilayer perceptrons; photographic process; photography; MUSIC parallel supercomputer; color correction; grey level correction; multilayer perceptron; neural network; photofinishing; photograph development; photograph finishing; Color; Costs; Databases; Laboratories; Multilayer perceptrons; Multiple signal classification; Neural networks; Printers; Production; Supercomputers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1996., IEEE International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-3210-5
Type :
conf
DOI :
10.1109/ICNN.1996.549237
Filename :
549237
Link To Document :
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