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Face Verification across Ages Using Self Organizing Map

B.Mahalakshmi, K.Duraiswamy, P.Gnanasuganya, P.Aruldhevi, R.Sundarapandiyan

Security system is a domain where often new technologies emerge and compete with each other to prove their excellence. Authentication using faces is an emerging trend in security systems where distinct facial features are extracted from the input image and searched with other images in the database for matching features. Since aging is uncontrollable, the techniques ‘Self Organizing Map (SOM)’ and ‘Dynamic Bayesian Networks (DBN)’ can be combining used to identify human faces across ages. This technique implements a weighted directed acyclic graph whose weight values represent similarities of the human faces taken into account. These weights are incrementally updated and learned using the training set of facial images of the same individual. In the beginning of the function, all weight vectors of the second layer neurons are set to random values. After that, some input-vector from the set of learning vectors is selected and set to the input of the Neural Network. At this step, the difference between the input vector and all neuron vectors of image in the face database is calculated. Thus, without any age limitations the exact output image matching the given input image is identified and the person is authenticated .The SOM technique can be effectively used in license renewal systems, online voting systems and other state applications reducing the human effort in a great concern.