Comparison of Paul Viola – Michael Jones algorithm and HOG algorithm for Face Detection

Abstract

The computer technology which helps to find the face of a person in video and image is face detection. It is like a biometric application that finds a person by analyzing and comparing the person’s face patterns. The face detection technique helps for security purposes, and also it has an rising interest in many fields. This technology has received good attention. It has some good applications based on law enforcement. For detecting face in an digital image, we have lot of algorithms. In this, Viola Jones algorithm and histogram of oriented gradients is used to detect the face of a person. The paper is proposed for a comparison between viola jones and Hog. By analyzing this we can find the gender, age and also emotions of the person. Here different type of images were used for detection. The Matlab tool and Jupyter is used for implementing this face detection process.

Haar Cascade Algorithm On Mask Detection System Based On Distance In Facing The Normal Era

“…For the image classifier process, the data needed is an image or object of a person wearing a mask and not wearing a mask. The creation of the dataset requires facial images before when the image is taken, the camera will only take pictures to be detected (PNithish Sriman et al, 2021). The collection of images is taken from the faces of friends from the Informatics Engineering Study Program, and video input it will be done with an open camera which can immediately detect whether the object uses a mask or not using a mask with a bounding box (Jemakmun et al, 2022).…”

Class Attendance System Based on Face Recognition

“…It is used to avoid the many arithmetic operations needed to calculate the (Haar feature), and this helps to quickly detect the features in the image. Instead of arithmetic operations to calculate each pixel, sub-rectangles are created, then matrices of these rectangles are created and finally used to calculate the values of Haar features [25]. However, not all of the Haar features are useful in the object identification process.…”

“…Where the images entered in the first filter level of the classifiers are calculated, if the result of the feature in the filter is negative, the input is rejected, while if the result is positive, it moves to the next filter level, and so on. Until the number of windows decreases and the face detection approaches [25,26]. Figure 2 shows the sequential classifier.…”