Open AccessA Simple Yet Reliable Facial Emotion Detection for Campus Environment
Author(s) -
Amar Lokman*,
Wan Zakiah Wan Ismail*,
Mus’ab Sahrim,
Sharma Rao Balakrishnan,
Juliza Jamaludin
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c4701.098319
Subject(s) - local binary patterns , computer science , face detection , face (sociological concept) , artificial intelligence , haar like features , computer vision , object class detection , image (mathematics) , simple (philosophy) , facial recognition system , pattern recognition (psychology) , histogram , social science , philosophy , epistemology , sociology
Nowadays, crime incidents like stealing, fighting and harassment often occur in campus leading to serious consequences. Students do not feel secure to study in campus anymore. Thus, a simple facial emotion detection system using a Raspberry Pi is introduced to help mitigating the issue before getting worse in campus. Two algorithms are used for this project including Haar Cascade and Local Binary Pattern (LBP) algorithms. OpenCV is a library that can be used for image processing. LBP algorithm is used for face detection in OpenCV. When a person enters the specified area, the camera will capture the image and detect the image of the person. Then, a rectangular box appears on the face image of the person. The image is automatically sent to the email. The face detection is enhanced by adding a face alignment. The face alignment is used to detect the location of many points on the face. It recognizes the emotions for each face and gives the confidence score. The value 0 of confidence score is the perfect face recognition. Although the system is simple, it is still reliable to be used in a campus environment.