This paper is published in Volume-5, Issue-3, 2019
Area
Information Technology
Author
G. Sumith Reddy
Co-authors
Devasani Aravind, Vanama Mohith, A. Sivajayaprakash
Org/Univ
SRM Institute of Science and Technology, Chennai, Tamil Nadu, India
Pub. Date
10 May, 2019
Paper ID
V5I3-1322
Publisher
Keywords
Surveillance architecture, Local binary pattern histogram, Open CV, Viola-Jones

Citationsacebook

IEEE
G. Sumith Reddy, Devasani Aravind, Vanama Mohith, A. Sivajayaprakash. Real time security surveillance using machine learning, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
G. Sumith Reddy, Devasani Aravind, Vanama Mohith, A. Sivajayaprakash (2019). Real time security surveillance using machine learning. International Journal of Advance Research, Ideas and Innovations in Technology, 5(3) www.IJARIIT.com.

MLA
G. Sumith Reddy, Devasani Aravind, Vanama Mohith, A. Sivajayaprakash. "Real time security surveillance using machine learning." International Journal of Advance Research, Ideas and Innovations in Technology 5.3 (2019). www.IJARIIT.com.

Abstract

As we know security has become a major concern in modern society. It is achieved by surveillance which is capable of taking brisk actions. This paper presents a new system architecture which provides real-time surveillance where unauthenticated people are differentiated and provides the data flow and storage path. Recognition errors are narrowed as much as possible to make the system work efficiently. The proposed approach exploits the Viola-Jones method for face detection, the LBPH (Local Binary Pattern Histogram) algorithm as feature tracker. This combination of algorithms gives more accuracy and less processing time in the proposed design. User data is stored separately from the trained file to make the system more reliable. The proposed design can be integrated into any place which is concerned about security and prevents the security breaches before they occur.
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