Levenberg-marquardt backpropagation neural network with techebycheve moments for face detection

Ali Nadhim Razzaq (Universiti Tun Hussein Onn Malaysia (UTHM))
Rozaida Ghazali (Universiti Tun Hussein Onn Malaysia (UTHM))
Nidhal Khdhair El Abbadi (University of Kufa)
Hussein Ali Hussein Al Naffakh (Universiti Tun Hussein Onn Malaysia (UTHM))

Bulletin of Electrical Engineering and Informatics
Vol 10, No 5: October 2021

Face detection is an intelligent approach used in a variety of applications that identifies human faces in digital images. This work presents a new method which composes of a neural network and Techebycheve transforms for face detection. For feature extraction, Tchebychev transform was applied, in which a discrete Tchebychev transform is given for different sampling patterns and several samples here were performed on color images. A Levenberg-Marquardt backpropagation neural network was applied to the transformed image to find faces in the face detection dataset and FDDB benchmarked database. Model performance was measured based on its accuracy and the best result from the newly proposed method was 98.9%. Simulation results showed that the proposed method handles face detection efficiently.