Fast Iris Detection Using Cooperative Modular Neural Nets

  • H. M. El-Bakry
Conference paper


In this paper, a combination of fast and cooperative modular neural nets to enhance the performance of the detection process is introduced. We have applied such approach successfully to detect human faces in cluttered scenes [10]. Here, this technique is used to identify human irises automatically in a given image. In the detection phase, neural nets are used to test whether a window of 20x20 pixels contains an iris or not. The major difficulty in the learning process comes from the large database required for iris / noniris images. A simple design for cooperative modular neural nets is presented to solve this problem by dividing these data into three groups. Such division results in reduction of computational complexity and thus decreasing the time and memory needed during the test of an image. Simulation results for the proposed algorithm show a good performance.


Cross Correlation Hide Neuron Iris Image Iris Detection Iris Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Wien 2001

Authors and Affiliations

  • H. M. El-Bakry
    • 1
  1. 1.Faculty of Computer Science & Information SystemsMansoura UniversityEgypt

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