Fast and Cost Efficient Face Detection System with CNN Using Raspberry PI
Pravin Kumar. S1, Bhuvaneswari Balachander2
1Pravin Kumar S Assistant Professor Electronics and Communication Engineering. Saveetha School of Engineering, SIMATS, Poonamalle, Chennai-602105.
2Ms. Bhuvaneswari Balachander, Assistant Professor for the department of ECE, Saveetha School of Engineering, SIMATS, Poonamalle, Chennai-602105.
Manuscript received on August 03, 2019. | Revised Manuscript received on August 22, 2019. | Manuscript published on August 30, 2019. | PP: 3037-3039 | Volume-8 Issue-6, August 2019. | Retrieval Number: F9034088619/2019©BEIESP | DOI: 10.35940/ijeat.F9034.088619
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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 detection is an important process when it comes to computer vision. It will serve as an input to a Facial expression and Face recognition system. Modern “C.C.T.V” cameras with face detection features are costly and only few are connected to the internet. This paper proposes a Face detection system which detects faces with a fusion of Convolutional neural network and Gabor Filter. Gabor filter is used to extract important facial features and Convolutional neural network is used to train the model. Model weights files are executed in Raspberry PI which is cost efficient. Raspberry pi is connected to cloud service which will alert the user with SMS and E-mail.
Keywords: Convolutional Neural Network, Cloud Service, Face Detection, Gabor filter, Raspberry Pi