Detection face parts in image using neural network based on MATLAB

Joint Authors

Ghalib, Shahd L.
Abd al-Rahman, Asma A.
Tahir, Fuad Sh.

Source

Engineering and Technology Journal

Issue

Vol. 39, Issue 1B (31 Jan. 2021), pp.159-164, 6 p.

Publisher

University of Technology

Publication Date

2021-01-31

Country of Publication

Iraq

No. of Pages

6

Main Subjects

Information Technology and Computer Science

Topics

Abstract EN

Recently, face recognition system (FRS) is implemented in different applications including a range of vital services like airports and banking systems for security purposes.

Therefore, deployed surveillance systems have been established which led to the urgent need to develop a vital face recognition system.

In this work, a new algorithm was proposed for recognition of the face, personal and color images by training the convolutional neural network using the MATLAB program to build a new program for detection of the face, then building a separate program to discover the lips, nose, and eyes, New methods were explored to analyze the main and independent components to improve face detection, which is considered one of the important techniques in this work using neural networks and implementation through the MATLAB program.

American Psychological Association (APA)

Ghalib, Shahd L.& Tahir, Fuad Sh.& Abd al-Rahman, Asma A.. 2021. Detection face parts in image using neural network based on MATLAB. Engineering and Technology Journal،Vol. 39, no. 1B, pp.159-164.
https://search.emarefa.net/detail/BIM-1282624

Modern Language Association (MLA)

Ghalib, Shahd L.…[et al.]. Detection face parts in image using neural network based on MATLAB. Engineering and Technology Journal Vol. 39, no. 1B (2021), pp.159-164.
https://search.emarefa.net/detail/BIM-1282624

American Medical Association (AMA)

Ghalib, Shahd L.& Tahir, Fuad Sh.& Abd al-Rahman, Asma A.. Detection face parts in image using neural network based on MATLAB. Engineering and Technology Journal. 2021. Vol. 39, no. 1B, pp.159-164.
https://search.emarefa.net/detail/BIM-1282624

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 164

Record ID

BIM-1282624