Home Security using Face Recognition Technology
Telugu Maddileti1, G. Shriphad Rao2, Vaddemani Sai Madhav3, Ganti Sharan4
1Telugu Maddileti, Assistant Professor, ECM Department, Sreenidhi Institute of Science and Technology, Ghatekesar, (Telangana), India.
2G. Shriphad Rao, ECM Department, Sreenidhi Institute of Science and Technology, Ghatekesar, (Telangana), India.
3Vaddemani Sai Madhav, ECM Department, Sreenidhi Institute of Science and Technology, Ghatekesar, (Telangana), India.
4Ganti Sharan, ECM Department, Sreenidhi Institute of Science and Technology, Ghatekesar, (Telangana), India.
Manuscript received on November 20, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 678-682 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B3917129219/2020©BEIESP | DOI: 10.35940/ijeat.B3917.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Face is the easiest way to penetrate each other’s personal identity. Face recognition is a method of personal identification using the personal characteristics of an individual to decide the identification of a person. The method of human face recognition consists basically of two levels, namely face detection and face recognition. There are three types of methods that are currently popular in the developed face recognition pattern, those are Eigen faces algorithm, Fisher faces algorithm and CNN neural network for face recognition
Keywords: Face recognition, Face-detection, Eigen-faces, Fisher-faces, CNN, Neural network, Residual network.