Low-Complexity Face Recognition using a Multilevel DWT and TwoStates of Continuous HMM to recognize Noisy Images
Hameed R. Farhan, H. Mahmuod, Al-Muifraje, Thamir Rashed Saeed · International Journal of Engineering and Technology · 2017
Face recognition has become an important subject in modern life, especially in security and surveillance applications.This work introduces a face recognition method, which is characterized by high-speed, low-complexity, and high-efficiency in a noisy environment.The performance of this method is greatly improved by using a median filter, such that each image is filtered to eliminate the influence of noise and light illumination.Multiple levels of discrete wavelet transform are applied to the filtered image to reduce size and eliminate further noise.Subsequently, the resultant image is scanned using a window with a predefined overlap in raster fashion to construct a sequence of observation vectors used as the basis of a model.The model consists of two states of a continuous hidden Markov model, a unique model in the face recognition field that has not yet been used by other researchers, which interprets the novelty and low complexity of the method.In spite of the presence of 0.15, 0.4, and 0.25 measurement values of impulse noise density in images stored in the ORL, Yale, and EURECOM Kinect face databases, respectively, the proposed work has achieved a recognition rate of 100%. Keywords-Face