Designing of Face Recognition System

Face Recognition is the most popular and trending technology in the present era. It is an effective way to provide vision to a machine for better interaction with humans. The way of living will be reflected if machines can read our faces. The face recognition system will move the world in a new dime...

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Vydáno v:2019 International Conference on Intelligent Computing and Control Systems (ICCS) s. 459 - 461
Hlavní autor: Sharma, Vijay Kumar
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.05.2019
Témata:
Computer vision
Conferences
Face
Face recognition
Feature extraction
Histograms
Kivy
LBPH
Local binary pattern (LBP)
OpenCV
Python
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Shrnutí:Face Recognition is the most popular and trending technology in the present era. It is an effective way to provide vision to a machine for better interaction with humans. The way of living will be reflected if machines can read our faces. The face recognition system will move the world in a new dimension. It will be beneficial in many ways to find the identity and security. In this paper, a face recognition system is proposed for advanced applications such as access and security, payments, criminal identifications etc. The process of identification will be based on face recognition which is further divided into three steps: detection of face, extractions of the features and classification, and real time recognition. Detection of face is recognized as the essential step of our system. It is used to extract a face in a frame, which is based on the Viola-Jones object detection algorithm that uses AdaBoost classifier with Haar and LBP features. Local Binary Patterns (LBP) is utilized to extract the unique features of the face like eyes, nose, and mouth in the feature extraction phase. The facial image is correlated with the images available in the database for the classification. The system is implemented in Python using OpenCV library. Kivy is used to create a user interface and also to build executables for different platforms.
DOI:10.1109/ICCS45141.2019.9065373