Exploration of Face Detection methods in Digital Images
C. Ruvinga1, D. Malathi2, J. D. Dorathi Jayaseeli3
1C. Ruvinga*, Computer Science and Engineering, Midlands State University, Gweru Zimbabwe.
2D. Malathi, Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur, India.
3J. D. Dorathi Jayaseeli, Computer Science and Engineering, SRM Institute of Science and Technology, Kattankulathur, India.

Manuscript received on November 17., 2019. | Revised Manuscript received on November 24 2019. | Manuscript published on 30 November, 2019. | PP: 12130-12136 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8014118419/2019©BEIESP | DOI: 10.35940/ijrte.D8014.118419

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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 a challenging computer vision task that identifies and localizes the faces of human beings from digital images or video streams. It is predominantly the first phase in the process of developing a wide range of face applications such as face recognition, emotion recognition, authentication, surveillance systems etc. The process of face detection is easy from the human perspective but, a complex task for computers that involves searching of the face in variable circumstances of pose, colour, size, occlusion, illumination etc. If the outcome of face detection is intended to be input for another algorithm, an accurate, well informed selection of an appropriate face detection technique is essential because the overall performance of face application is dependent on face detection algorithm’s precision. The survey paper presents a review of three commonly used face detection algorithms available in literature namely Viola Jones, Neural networks (NN) and Local Binary Pattern (LBP) for the purpose of ascertaining the most suitable face detection algorithm to implement for our future work in developing an ‘Online student concentration level recognition system’.
Keywords: Computer Vision, Face Detection, Local Binary Pattern (LBP), Neural Networks (NN), Viola and Jones.
Scope of the Article: Foundations of Communication Networks.