Face Detection and Recognition using Open CV Based on Fisher Faces Algorithm
J. Manikandan1, S. Lakshmi Prathyusha2, P. Sai Kumar3, Y. Jaya Chandra4, M. Umaditya Hanuman5

1J. Manikandan, Assistant Professor, department of CSE, Koneru Lakshmaiah University
2S. Lakshmi Prathyusha, B. Tech, CSE Department, Koneru Lakshmaiah University
3P. Sai Kumar, B. Tech, CSE Department, Koneru Lakshmaiah University
4Y. Jaya Chandra, B. Tech, CSE Department, Koneru Lakshmaiah University
5M. Umaditya Hanuman, B. Tech, CSE Department, Koneru Lakshmaiah University.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 1204-1208 | Volume-8 Issue-5, January 2020. | Retrieval Number: E5753018520/2020©BEIESP | DOI: 10.35940/ijrte.E5753.018520

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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: Facial Recognition represents the event of a system which may determine the person with the assistance of a face using Computer Vision (Open CV). Face recognition is employed within the fields of Identity Recognition, police investigation and enforcement. It’s a method of characteristic someone supported facial expression. This method is enforced in 2 stages. They’re the training stage and therefore the testing stage. This study primarily consists of 3 elements, specifically face detection from the image, feature extraction and storing many reminder images, and recognition. Face finding rule is employed to detect the face from the given image. The foremost helpful and distinctive options of the face image are extracted within the feature extraction part. Face Detection may be challenging because of pictures and video frames will contain advanced background, completely different head poses and occlusion like carrying glasses or scarf. It presents a rule for finding face recognition downside and concatenated into one feature vector that is employed to coach the system to recognise among the prevailing photos with it. Within the testing stage the system takes the face of the image of someone for recognition. Image acquisition, pre-processing, image filtering, feature extraction is just like the learning stage. For classification the options are fed to the trained system. The algorithms can determine the face image from the content and acknowledges it.
Keywords: Feature Extraction, Occlusion, Pre-Processing, And Image Filtering.
Scope of the Article: Digital Signal Processing Theory.