Surveillance System with Impediment of Face Discovery Using Python

Authors

  • Sital Prasad Mandal Department Of Computer Science & Application Mechi Multiple Campus, Bhadrapur, Jhapa, Nepal
  • Sunil Sharma Department of Computer Science and Application Mechi Multiple Campus, Bhadrapur, Jhapa Tribhuvan University, Nepal

DOI:

https://doi.org/10.3126/aj.v11i11.67084

Keywords:

Neural Networks, Graph Matching, Facial Recognition, Combined Classifiers

Abstract

In recent years, It is an active area of research and development with there ongoing and active work on computer vision. This paper presents an empirical literature review of the existing research on human facial recognition as up-to-date. This research start providing the reader with a brief on the uses and working of face recognition. The most recent approaches to facial recognition are then reviewed in the literature. The performance and drawbacks of these face recognition algorithms are also tested through use of the Labelled Wild Face (LWF) face dataset images as well as real time images. With the increasing use of real-time facial recognition systems, it is important to examine the accuracy of these systems given the reliability and 94.23% accuracy are achieved for facial recognition by the proposed model.

Downloads

Download data is not yet available.
Abstract
180
pdf
69

Downloads

Published

2024-06-25

How to Cite

Mandal, S. P., & Sharma, S. (2024). Surveillance System with Impediment of Face Discovery Using Python. Adhyayan Journal, 11(11), 93–104. https://doi.org/10.3126/aj.v11i11.67084

Issue

Section

Articles