Abstract
Faces blurring is one of the important complex processes that is considered one of the advanced computer vision fields. The face blurring processes generally have two main steps to be done. The first step has detected the faces that appear in the frames while the second step is tracking the detected faces which based on the information extracted during the detection step. In the proposed method, an image is captured by the camera in real time, then the Viola Jones algorithm used for the purpose of detecting multiple faces in the captured image and for the purpose of reducing the time consumed to handle the entire captured image, the image background is removed and only the motion areas are processed. After detecting the faces, the Color-Space algorithm is used to tracks the detected faces depending on the color of the face and to check the differences between the faces the Template Matching algorithm was used to reduce the processes time. Finally, thedetected faces as well as the faces that were tracked based on their color were obscured by the use of the Gaussian filter. The achieved accuracy for a single face and dynamic background are about 82.8% and 76.3% respectively.
Highlights
In recent years, the researches that contain human face in the field of image processing have been grown in terms of interest, because of the establishment and development of some approaches such perceptual user interfaces and security applications, compression, and some others”
In 2017, Yee write a thesis titled "Cascaded Facial Detection Algorithms to Improve Recognition", it compares between three different types of facial detection algorithms Viola-jones algorithm, histogram of gradient algorithm, skin segmentation which “combined in various configuration to test all the accuracy for the detection faces at the execution time giving it into a convolution neural network” which make it easy to identifying who is that person
This research aims to protect the privacy by blur multiple faces in real time using Gaussian noise for blurring, Viola-Jones for detection and Color space for tracking
Summary
The researches that contain human face in the field of image processing have been grown in terms of interest, because of the establishment and development of some approaches such perceptual user interfaces and security applications, compression, and some others”. In 2010, Niazi and Jafari, propose a Hybrid face detection algorithm that could detect faces in color images with different complex backgrounds and lights. In 2013, Makovetsky and Petrosyan, presented a "Face Detection and Tracking with Web Camera", they use Viola-Jones algorithm for detecting the faces. They use pixel sampling method to make this algorithm work faster by reduced the image size. Their system processes work on 8 frames per second and it is enabled to detect multiple faces and tracking all of them in real time.
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