Biometric authentication data with three traits using compression technique, HOG, GMM and fusion technique

This paper presents a three trait identification model called multimodal recognition system developed by using different traits like face, finger and voice (Babu and Naidu, 2014, 2016; Balaka and Surendra, 2017) [1–3]. This system provides more security when compare to existing works. Initially, all the traits are followed by pre-processed, extract features using Histogram of oriented gradients (HOG), then apply Gaussian mixture model (GMM) for finding probability density function (PDF) values and then combining these features by using Score level fusion. The result of these features considered as a trainee dataset. In verification process, each test image trait compare with the trainee dataset. This entire process of authentication is done by using machine learning based technique.