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All Journal Bulletin of Electrical Engineering and Informatics
Ali Nadhim Razzaq
Universiti Tun Hussein Onn Malaysia (UTHM)
Electrical & Electronics Engineering

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Levenberg-marquardt backpropagation neural network with techebycheve moments for face detection Ali Nadhim Razzaq; Rozaida Ghazali; Nidhal Khdhair El Abbadi; Hussein Ali Hussein Al Naffakh
Bulletin of Electrical Engineering and Informatics Vol 10, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i5.2364

Abstract

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.
Co-Authors Hussein Ali Hussein Al Naffakh Nidhal Khdhair El Abbadi Rozaida Ghazali