Optimisation Using Levenberg-Marquardt Algorithm of Neural Networks for Iris

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 247)


This paper explores the optimisation technique of Damped Least Square Method also known as the Levenberg-Marquardt (LM) Algorithm for Iris recognition. The motive behind it is to show that even though there are many algorithms available which act as an alternative to the LM algorithm such as the simple gradient decent and other conjugate gradient methods be it the vanilla gradient decent or the Gauss Newton iteration, the LM algorithm outperforms these optimisation techniques due to the addressing of the problem by the algorithm as the Non-linear Least Square Minimisation. The results are promising and provide an insight into Iris recognition which are distinct pattern of individuals and are unique in case of every eye.


Levenberg-Marquardt LM algorithm Iris Biometrics of the eye Optimisation of Iris Images Least square method for Iris Damped Least Square Non Linear Least Square Method 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Electronics & TelecommunicationSAOEPuneIndia
  2. 2.Department of Computer EngineeringAISSMS IOITPuneIndia

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