An Improved Face Detection Method Based on Face Recognition Application

2019 ◽  
Author(s):  
Qinfeng Li
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Detection Method

scholarly journals Face Recognition Based on Viola-Jones Face Detection Method and Local Binary Pattern (LBP)

2019 ◽  
pp. 50-55
Keyword(s):  
Feature Extraction ◽  
Face Recognition ◽  
Face Detection ◽  
Local Binary Pattern ◽  
Detection Method ◽  
Histogram Equalization ◽  
Face Image ◽  
Accuracy Rate ◽  
Data Set ◽  
Testing Phase

In this paper, the system consists of many steps, the first step includes the histogram equalization, detection, feature extraction, and classification. At first, the data set of a face image is segmented into four segments, after that Local Binary Pattern (LBP) algorithm is performed to extract features for each segment. The best feature vectors for all persons are stored in a new dataset in the next stage in order to be used in the testing phase. Finally, the accuracy rate of performance is evaluated to prove its robustness. Experiments show satisfying results and more accuracy achieved by the paper.

scholarly journals Face Detection

2020 ◽  
Vol 5 (9) ◽  
pp. 688-692
Author(s):  
Amir Nobahar Sadeghi Nam
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Face Recognition ◽  
Face Detection ◽  
Main Part ◽  
Detection Method ◽  
Input Image ◽  
Effective Algorithm ◽  
Human Faces

Face detection is one of the challenging problems in the image processing, as a main part of automatic face recognition. Employing the color and image segmentation procedures, a simple and effective algorithm is presented to detect human faces on the input image. To evaluate the performance, the results of the proposed methodology is compared with ViolaJones face detection method.

scholarly journals Using Rasberry Pi 3 And Face Detection Method To Take The Attendance Of The Student In The Classroom And Other Security Purposes

2018 ◽  
Vol 1 (6) ◽  
pp. 100-100
Author(s):  
Debopama Ghosh ◽  
Arkaprabha Lodh ◽  
Debosama Ghosh
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Current Problem ◽  
Detection Method ◽  
Important Task ◽  
Productive Time

Attendance for the students is an important task in class. When done manually it generally wastes a lot of productive time of the class. This proposed solution for the current problem is to automation of attendance system using face recognition. Face is the main identification for any human to know

Real AdaBoost face detection method based on multi-threshold

2009 ◽  
Vol 29 (8) ◽  
pp. 2098-2100
Author(s):  
Shi-ming SUN ◽  
Qing PAN ◽  
You-fang JI
Keyword(s):  
Face Detection ◽  
Detection Method ◽  
Real Adaboost

Pose estimation and frontal face detection for face recognition

2005 ◽  
Author(s):  
Eng Thiam Lim ◽  
Jiangang Wang ◽  
Wei Xie ◽  
Venkarteswarlu Ronda
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Pose Estimation

The Adaboost Algorithm Applied in ATM Automatic Identification System

2013 ◽  
Vol 753-755 ◽  
pp. 2941-2944
Author(s):  
Ming Hui Zhang ◽  
Yao Yu Zhang
Keyword(s):  
Face Recognition ◽  
Face Detection ◽  
Computing Time ◽  
Automatic Identification ◽  
Identification System ◽  
Human Face ◽  
Detection Experiment ◽  
Adaboost Algorithm ◽  
Face Features ◽  
Human Faces

Seeing that human face features are unique, an increasing number of face recognition algorithms on existing ATM are proposed. Since face detection is a primary link of face recognition, our system adopts AdaBoost algorithm which is based on face detection. Experiment results demonstrated that the computing time of face detection using this algorithm is about 70ms, and the single and multiple human faces can be effectively measured under well environment, which meets the demand of the system.

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