Applied Intelligence

, Volume 18, Issue 2, pp 195–213

Image Processing Using RBF like Neural Networks: A ZISC-036 Based Fully Parallel Implementation Solving Real World and Real Complexity Industrial Problems


  • Kurosh Madani
    • Intelligence in Instrumentation and Systems—I2S, SENART Institute of TechnologyUniversity PARIS XII
  • Ghislain de Trémiolles
    • IBM France, Laboratoire d'Etude et de Developpement
  • Pascal Tannhof
    • IBM France, Laboratoire d'Etude et de Developpement

DOI: 10.1023/A:1021990410058

Cite this article as:
Madani, K., de Trémiolles, G. & Tannhof, P. Applied Intelligence (2003) 18: 195. doi:10.1023/A:1021990410058


The present article concerns neural based image processing and solutions developed for industrial problems using the ZISC-036 neuro-processor, an IBM hardware processor which implements the Restricted Coulomb Energy algorithm (RCE) and the K-Nearest Neighbor algorithm (KNN). The developed neural based techniques have been applied for image enhancement in order to restore old movies (noise reduction, focus correction, etc.), to improve digital television images, or to treat images which require adaptive processing (medical images, spatial images, special effects, etc.). We also have developed and implemented on ZISC-036 neuro-processor, a neural network based solution for visual probe mark inspection in VLSI production for the IBM Essonnes plant. The main characteristics of such systems are real-time control and high reliability in detection and classification tasks. Experimental results, validating presented concepts, have been reported showing quantitative and qualitative improvement as well as the efficiency our solutions.

image processingneural networksZISC-036 neuro-processorreal-time processingindustrial application
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© Kluwer Academic Publishers 2003