FACE RECOGNITION APPLICATION BASED ON EMBEDDED SYSTEM

FACE RECOGNITION APPLICATION BASED ON EMBEDDED SYSTEM

Bibliographic Details
Main Author: Gao, Weihao
Language:English
Published: Case Western Reserve University School of Graduate Studies / OhioLINK 2013
Subjects:
Computer Engineering
Computer Science
Android
OpenCV
Adaboost
Face recognition
PCA
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=case1385462534
id ndltd-OhioLink-oai-etd.ohiolink.edu-case1385462534
record_format oai_dc
spelling ndltd-OhioLink-oai-etd.ohiolink.edu-case13854625342021-08-03T06:20:37Z FACE RECOGNITION APPLICATION BASED ON EMBEDDED SYSTEM Gao, Weihao Computer Engineering Computer Science Android OpenCV Adaboost Face recognition PCA The purpose of this application is to develop an embedded system application which is able to collect face image and recognize the face by comparing with the database inside the system. Face recognition as a type of biometric methods has the features of non-contact, safety and convenience. It is widely used in human-computer interaction, transaction authentication, security and other fields. Recent years, with the development of mobile internet and embedded computer, it becomes possible to run face recognition on embedded system. This type of application has huge potential in remote payment and personal information security. This application is running on Android operating system which is an operating system based on the Linux kernel, and designed primarily for touchscreen mobile devices such as smartphones and tablet computers. The procedure of face recognition includes face detection, face normalization and recognition. This paper studies these key issues and successfully developed an application with nice recognition rate. The main contents and results are as follows:1) Discusses the face detection method. It used Adaboost algorithm and Haar features to detect human faces.2) Studies image pre-processing methods. Standardize the images so as to minimize the storage space and speed up the computation speed. 3) Summarize a variety of face recognition algorithms especially principle component analysis which is used in this application. Discuss the theoretical foundation of PCA algorithm. 4) Fulfilled all the features from face detection to recognition in Android platform. Using ORL face image database for testing and got a correct identification rate of over 85%. Fully verify the effectiveness of the program. Discuss the results and identification strategies. 2013 English text Case Western Reserve University School of Graduate Studies / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=case1385462534 http://rave.ohiolink.edu/etdc/view?acc_num=case1385462534 unrestricted This thesis or dissertation is protected by copyright: some rights reserved. It is licensed for use under a Creative Commons license. Specific terms and permissions are available from this document's record in the OhioLINK ETD Center.
collection NDLTD
language English
sources NDLTD
topic Computer Engineering
Computer Science
Android
OpenCV
Adaboost
Face recognition
PCA
spellingShingle Computer Engineering
Computer Science
Android
OpenCV
Adaboost
Face recognition
PCA
Gao, Weihao
FACE RECOGNITION APPLICATION BASED ON EMBEDDED SYSTEM
author Gao, Weihao
author_facet Gao, Weihao
author_sort Gao, Weihao
title FACE RECOGNITION APPLICATION BASED ON EMBEDDED SYSTEM
title_short FACE RECOGNITION APPLICATION BASED ON EMBEDDED SYSTEM
title_full FACE RECOGNITION APPLICATION BASED ON EMBEDDED SYSTEM
title_fullStr FACE RECOGNITION APPLICATION BASED ON EMBEDDED SYSTEM
title_full_unstemmed FACE RECOGNITION APPLICATION BASED ON EMBEDDED SYSTEM
title_sort face recognition application based on embedded system
publisher Case Western Reserve University School of Graduate Studies / OhioLINK
publishDate 2013
url http://rave.ohiolink.edu/etdc/view?acc_num=case1385462534
work_keys_str_mv AT gaoweihao facerecognitionapplicationbasedonembeddedsystem
_version_ 1719434899497156608

Similar Items