Gamma Effect in Face Detection Methods

Document Type : Reviews Articles.

Authors

1 Electrical,engineering ,south valley university

2 Adel B. Abdel-Rahman School of Electronics, Communications and Computer Engineering E-JUST,Egypt ‫ adel.bedair@ejust.edu.eg‬‬

3 Mohamed Abdel-Nasser Faculty of Engineering Aswan University Aswan , Egypt mohamed.abdelnasser@aswu.edu.eg

Abstract

A face detection could be a technology capable of find a person's face in image or video frame. Face detection is one in all the foremost widely used computer vision applications. it's a fundamental problem in computer vision and pattern recognition. Face detection could be a critical beginning in face recognition systems, with the reason for localizing and extracting the face location from the background. within the last decade, multiple face feature detection methods are introduced. In python, there are plenty of methods for face detection like as OpenCV library, dlib library , MTCNN algorithm ,and ….etc. during this paper, we present a compression between the face detection methods. There are many face detection methods. we decide the foremost used like OpenCV with Haar cascade and LBP models, MTCNN algorithm and dlib with CNN model and HOG model in python and therefore the effect of gamma value on its accuracy. The chosen face detection methods measured the period of time for each gamma value.

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