TY - JOUR
T1 - Real time face recognition of video surveillance system using haar cascade classifier
AU - Ahmad, Adlan Hakim
AU - Saon, Sharifah
AU - Mahamad, Abd Kadir
AU - Darujati, Cahyo
AU - Mudjanarko, Sri Wiwoho
AU - Susiki Nugroho, Supeno Mardi
AU - Hariadi, Mochamad
N1 - Publisher Copyright:
© 2021 Institute of Advanced Engineering and Science. All rights reserved.
PY - 2021/3
Y1 - 2021/3
N2 - This project investigates the use of face recognition for a surveillance system. The normal video surveillance system uses in closed-circuit television (CCTV) to record video for security purpose. It is used to identify the identity of a person through their appearances on the recorded video, manually. Today’s video surveillance camera system usually not occupied with a face recognition system. With some modification, a surveillance camera system can be used as face detection and recognition that can be done in real-time. The proposed system makes use of surveillance camera system that can identify the identity of a person automatically by using face recognition of Haar cascade classifier. The hardware used for this project were Raspberry Pi as a processor and Pi Camera as a camera module. The development of this project consist of three main phases which were data gathering, training recognizer, and face recognition process. All three phases have been executed using Python programming and OpenCV library, which have been performed in a Raspbian operation system. From the result, the proposed system successfully displays the output result of human face recognition, with facial angle within ±40°, in medium and normal light condition, and within a distance of 0.4 to 1.2 meter. Targeted image are allowed to wear face accessory as long as not covering the face structure. In conclusion, this system considered, can reduce the cost of manpower in order to identify the identity of a person in real time situation.
AB - This project investigates the use of face recognition for a surveillance system. The normal video surveillance system uses in closed-circuit television (CCTV) to record video for security purpose. It is used to identify the identity of a person through their appearances on the recorded video, manually. Today’s video surveillance camera system usually not occupied with a face recognition system. With some modification, a surveillance camera system can be used as face detection and recognition that can be done in real-time. The proposed system makes use of surveillance camera system that can identify the identity of a person automatically by using face recognition of Haar cascade classifier. The hardware used for this project were Raspberry Pi as a processor and Pi Camera as a camera module. The development of this project consist of three main phases which were data gathering, training recognizer, and face recognition process. All three phases have been executed using Python programming and OpenCV library, which have been performed in a Raspbian operation system. From the result, the proposed system successfully displays the output result of human face recognition, with facial angle within ±40°, in medium and normal light condition, and within a distance of 0.4 to 1.2 meter. Targeted image are allowed to wear face accessory as long as not covering the face structure. In conclusion, this system considered, can reduce the cost of manpower in order to identify the identity of a person in real time situation.
KW - Closed circuit television
KW - Face recognition
KW - Harr cascaded classifier
KW - Raspberry Pi
KW - Surveillance camera
UR - http://www.scopus.com/inward/record.url?scp=85102510774&partnerID=8YFLogxK
U2 - 10.11591/ijeecs.v21.i3.pp1389-1399
DO - 10.11591/ijeecs.v21.i3.pp1389-1399
M3 - Article
AN - SCOPUS:85102510774
SN - 2502-4752
VL - 21
SP - 1389
EP - 1399
JO - Indonesian Journal of Electrical Engineering and Computer Science
JF - Indonesian Journal of Electrical Engineering and Computer Science
IS - 3
ER -