Abstract
Today, the world has become a place of uncertainty. With digitalizing the work architecture, there is high need for advancing the physical security of the organization too. The main reason behind this research is the issue of centralization of data inside the office within servers, physical files, etc. Ultimately the motive of an organization is protection from potential data theft and destruction and also security of their employees. The security guards play an important role in this, but human beings make mistakes. Thus, digitizing this system is the only way to keep up the level. This system leverages the image recognition technique to process every individual and filter the intruders from entering inside the organization. The CCTV camera propagates the real-time video streaming for processing to the face recognition engine and compares with existing models of regular persons (registered persons). For the research, we have used ID card detection for an additional layer of security.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Azeta AA, Omoregbe NA, Adewumi AO, Oguntade D (2015) Design of a face recognition system for security control. In: International conference on African development issues (CU-ICADI) 2015: information and communication technology track, pp 55–57
Face Recognition Using Transfer Learning with VGG16—Shikhar Srivastava
Habibzadeh M, Jannesari M, Rezaei Z, Baharvand H, Totonchi M (2018) Automatic white blood cell classification using pre-trained deep learning models: resnet and inception. In: Tenth international conference on machine vision (ICMV 2017) 2018 Apr 13, vol 10696. International Society for Optics and Photonics, p 1069612
Zhang S, Wen L, Bian X, Lei Z, Li SZ. Single-shot refinement neural network for object detection
Law H, Teng Y, Russakovsky O, Deng J (2019) CornerNet-lite: efficient keypoint based object detection. arXiv preprint arXiv:1904.08900
Learn TensorFlow 2.0: Implement machine learning and deep learning models with python
Szegedy C, Liu W, Jia Y, Sermanet P, Reed S, Anguelov D, Erhan D, Vanhoucke V, Rabinovich A (2015) Going deeper with convolutions. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1–9
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Taluja, A., Singhal, J., Gulati, A., Gupta, H. (2022). Gatekeeper Security Check System Using VGG. In: Zhang, YD., Senjyu, T., So-In, C., Joshi, A. (eds) Smart Trends in Computing and Communications. Lecture Notes in Networks and Systems, vol 286. Springer, Singapore. https://doi.org/10.1007/978-981-16-4016-2_66
Download citation
DOI: https://doi.org/10.1007/978-981-16-4016-2_66
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-4015-5
Online ISBN: 978-981-16-4016-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)