TY - GEN
T1 - Diseño e Implementación de un sistema de identificación de personas para la seguridad de los accesos a condominios, basado en el algoritmo de reconocimiento facial LBPH Faces
AU - Verdeguer-Valderrama, Diego
AU - Campos-Vasquez, Neicer
N1 - Publisher Copyright:
© 2021 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.
PY - 2021
Y1 - 2021
N2 - The purpose of the work presented below is the design and implementation of a person identification system for the security of access to condominiums, based on the LBPHFaces facial recognition algorithm. Different research works were identified with respect to facial recognition for the safety of people and thus analyze the algorithmic methods they used. 300 images of the faces of the people that the system will identify were captured and stored in a repository with the name of the person's face. The algorithm identifies the faces, transforms the images to grayscale and trains them to identify if the face in real time displayed by the surveillance camera has similarity to the images trained within the repository. The 3 most used methods were analyzed, which are the FisherFaces, EigenFaces and the LBPHFaces. In the end, the results yielded very positive values with respect to the chosen algorithms, and it was concluded that the LBPHFaces was superior to the other two mentioned in response time, training and percentage of hits, which makes it the most reliable for the safety of the people.
AB - The purpose of the work presented below is the design and implementation of a person identification system for the security of access to condominiums, based on the LBPHFaces facial recognition algorithm. Different research works were identified with respect to facial recognition for the safety of people and thus analyze the algorithmic methods they used. 300 images of the faces of the people that the system will identify were captured and stored in a repository with the name of the person's face. The algorithm identifies the faces, transforms the images to grayscale and trains them to identify if the face in real time displayed by the surveillance camera has similarity to the images trained within the repository. The 3 most used methods were analyzed, which are the FisherFaces, EigenFaces and the LBPHFaces. In the end, the results yielded very positive values with respect to the chosen algorithms, and it was concluded that the LBPHFaces was superior to the other two mentioned in response time, training and percentage of hits, which makes it the most reliable for the safety of the people.
KW - Confidence level
KW - Facial recognition
KW - LBPH faces algorithm
UR - http://www.scopus.com/inward/record.url?scp=85122036701&partnerID=8YFLogxK
U2 - 10.18687/LACCEI2021.1.1.213
DO - 10.18687/LACCEI2021.1.1.213
M3 - Contribución a la conferencia
AN - SCOPUS:85122036701
T3 - Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
BT - 19th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology
A2 - Larrondo Petrie, Maria M.
A2 - Zapata Rivera, Luis Felipe
A2 - Aranzazu-Suescun, Catalina
T2 - 19th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: "Prospective and Trends in Technology and Skills for Sustainable Social Development" and "Leveraging Emerging Technologies to Construct the Future", LACCEI 2021
Y2 - 19 July 2021 through 23 July 2021
ER -