Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : face detection

Smart Door for Handicapped People via Face Recognition and Voice Command Technique

Hanaa M. Salman; Rana T. Rasheed

Engineering and Technology Journal, 2021, Volume 39, Issue 1B, Pages 222-230
DOI: 10.30684/etj.v39i1B.1719

Smart home indicates an application for different technological implementations, it could indicate any system which controls the door lock and several other devices. Facial identification which is an important section to achieve surveillance and safety, especially for handicapped people, can be considered as one of the ways that deal with biometrics and performed to identify facial images via utilizing fundamental features of the face. A Raspberry Pi-based face recognition system using conventional face detection and recognition techniques is going to be supplied, so the method in which image-built biometrics uses a Raspberry Pi is described. The aim of the paper here can be considered as transferring face recognition to a level in which the system can replace the utilizing of RF I-Cards and a password to access any system of security and making the system alive and protect the door from being open by hackers, especially by using the picture of an authorized person, we make the raspberry pi turn off and cannot turn on only by a command from the authorized person's mobile. The result of the presented proposal is a system that uses face recognition by utilizing OpenCV, Raspberry Pi, and it functions on an application of Android, and this system percentage becomes 99.63%. It should be cost-effective, of high performance, secured, and easy to use, which can be used in any smart home application.

Detection Face Parts in Image Using Neural Network Based on MATLAB

Shahad L. Galib; Fouad S. Tahir; Asma A. Abdulrahman

Engineering and Technology Journal, 2021, Volume 39, Issue 1B, Pages 159-164
DOI: 10.30684/etj.v39i1B.1944

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.

Face Recognition for Authentication by Using Anthropometric Model

Hussien; Farah Tawfiq Abd El; Emad K. Jabbar

Engineering and Technology Journal, 2010, Volume 28, Issue 11, Pages 2196-2205

This paper presents an automatic technique for detecting important facial
features’ points using a developed anthropometric face model. The facial
features’ points we work on are about the areas of mouth, nose, eyes and
eyebrows. The anthropometric means the scientific study of the measurements
and proportions of the human face. Several processes are performed in order
to recognize human personality authenticated or not, these processes are
beginning by capturing colored image using fixed digital camera and ending
by features isolated into separated sub images and the lengths and distances
among them representing authenticated persons information are stored into
In authentication stage all the extracted features are compared with stored
authenticated facial features in the database, the person is authenticated if a
percentage of similarity equal to or greater than 78% is achieved.