On the Use of a Low-Cost Embedded System for Face Detection and Recognition

2020 ◽  
Author(s):  
Ramiro Sandoval ◽  
Vanessa Camino ◽  
Ricardo Flores Moyano ◽  
Daniel Riofrio ◽  
Noel Perez ◽  
...  
Keyword(s):  
Embedded System ◽  
Face Detection ◽  
Low Cost ◽  
Face Detection And Recognition ◽  
Detection And Recognition

Optical face detection and recognition system on low-end-low-cost Xilinx Zynq SoC

Optik ◽  
2020 ◽  
Vol 217 ◽  
pp. 164747
Author(s):  
Kortli Yassin ◽  
Jridi Maher ◽  
Merzougui Mehrez ◽  
Atri Mohamed
Keyword(s):  
Face Detection ◽  
Low Cost ◽  
Recognition System ◽  
Face Detection And Recognition ◽  
Detection And Recognition

scholarly journals Smart E-Attendance System Utilizing Eigenfaces Algorithm

2018 ◽  
pp. 56-63
Keyword(s):  
Face Detection ◽  
High Efficiency ◽  
Low Cost ◽  
Advanced Technology ◽  
Educational Institutions ◽  
Microsoft Access ◽  
Face Detection And Recognition ◽  
Educational Field ◽  
Detection And Recognition

With the development of technologies and the availability of internet in the present era, the human has been looking for ease and efficiency in running his business, the educational field has been affected by a radical revolution as a result of the introduction of advanced technology. This has led educational institutions to provide and utilize all methods of advanced technology. This paper suggests a simple way of taking students attendance in universities and schools by using face detection and recognition with the goal of checking student’s attendance in the classroom automatically. This operation is done with low cost because there is no need for special hardware to install the system in the classroom. It can be applied using a computer and a camera with low effort and high efficiency. Eigenfaces algorithm is applied in the proposed system for face detection and recognition utilizing OpenCV libraries and Visual C#.Net 2015 with Microsoft Access 2016.

scholarly journals PEMANFAATAN RASPBERRY PI SEBAGAI PROCESSOR PADA PENDETEKSIAN DAN PENGENALAN POLA WAJAH

2016 ◽  
Vol 7 (3) ◽  
Author(s):  
Fadli Sirait ◽  
Yoserizal Yoserizal
Keyword(s):  
Discriminant Analysis ◽  
Embedded System ◽  
Face Detection ◽  
Principal Component ◽  
Raspberry Pi ◽  
Cascade Classifier ◽  
Linear Discriminant ◽  
Face Detection And Recognition ◽  
Haar Cascade ◽  
Detection And Recognition

Teknologi biometrik adalah teknologi untuk mengindetifikasi mahluk hidup. Tujuan perancangan  adalah  untuk  membangun  sistem  pendeteksi  wajah  dari  objek  citra  yang  didapat dari  gambar  frame  video  melalui  kamera.  Kemudian  dilakukan  pendeteksi  pola  wajah  yang dikenali  dan  mencari  kemiripan  terhadap  database  model  wajah  menggunakan  Raspberri  Pi berbasis  penggunaan  perangkat  lunak  Free  dan  Opensource.  Perancangan  ini  menggunakan metode  pengenalan  objek  citra  wajah  dengan  Haar  Cascade  Classifier  yang  diimplentasikan pada libarary OpenCV, sedangkan metode pengenalan pola wajah dengan menggunakan analisa PCA (Principal Component Analysist) dan LDA (Linear Discriminant Analysis) menggunakan pemograman  prerangkat  lunak  yang  dibuat  berbasis  Python.  Perangkat  lunak  yang dikembangkan  juga  dijalankan  pada  sistem  operasi  berbasis  Linux  Raspbian  (Jessie  dan Wheezy)  yang  diinstal  di  Raspberry  Pi.  Proses  input  citra  menggunakan  USB  kamera  yang dipasang  pada  Raspberry  Pi  2  Model  B  yang  dilengkapi  dengan  LCD  3,5  inchi.  Berdasarkan data pengujian terhadap 127 input didapat tingkat akurasi untuk pendeteksian satu objek wajah 84-97% sementara performa penggunaan CPU pada Raspberry Pi 41.87-46.25%.Kata kunci: face detection and recognition, Raspberry pi, pengolahan citra, embedded system.

A Novel Approach of Face Detection Based on Skin Color Segmentation and SVM

2011 ◽  
Vol 225-226 ◽  
pp. 437-441
Author(s):  
Jing Zhang ◽  
You Li
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Information Access ◽  
Color Segmentation ◽  
Support Vector ◽  
Svm Classifier ◽  
Novel Approach ◽  
Great Performance ◽  
Face Detection And Recognition ◽  
Detection And Recognition

Nowadays, face detection and recognition have gained importance in security and information access. In this paper, an efficient method of face detection based on skin color segmentation and Support Vector Machine(SVM) is proposed. Firstly, segmenting image using color model to filter candidate faces roughly; And then Eye-analogue segments at a given scale are discovered by finding regions which are darker than their neighborhoods to filter candidate faces farther; at the end, SVM classifier is used to detect face feature in the test image, SVM has great performance in classification task. Our tests in this paper are based on MIT face database. The experimental results demonstrate that the proposed method is encouraging with a successful detection rate.

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