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Enhancing Facial Detection and Recognition: Leveraging OpenCV and CNNs for Efficient Analysis

Vol 3 , Issue 1 , January - June 2023 | Pages: 70-80 | Research Paper  

https://doi.org/10.17492/computology.v3i1.2307


Author Details ( * ) denotes Corresponding author

1. P. Srinadh, Department of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India (srinadhpippalla1911@gmail.com)
2. B. Sai Pavan, Department of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India (2000031741@klunivrsity.in)
3. B. Naga Sai Chaitanya, Department of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India (2000032062@kluniversity.in)
4. V. Vidyadhar, Department of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India (2000032068@kluniversity.in)
5. * G. R. Anantha Raman, Department of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India (anantharamangr@kluniversity.in)
6. Senthil Athithan, Department of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India (senthilathithan@kluniversity.in)

This paper presents an optimal method for the detection and recognition of human faces by harnessing the capabilities of OpenCV and Python, which are integral deep learning tools. This research delves into an exhaustive exploration of diverse approaches in this context. This research investigates the various ways. Deep learning, an important component of computer science, can to determine the face, several OpenCV libraries may be utilised. Python is also employed. This paper will present a suggested system. This will facilitate real-time human face detection, and this approach can be easily applied to a diverse array of platforms, spanning machines, mobile devices, and software applications. Index Terms—Detecting faces, recognising faces, CNN, OpenCV, Machine Learning, HAAR Cascade algorithm.

Keywords

Detecting faces; Recognising faces; CNN; OpenCV; Machine Learning; HAAR Cascade algorithm


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