Introduction:
Face Detection is used in many different steams like video conferencing, human-computer
interface, in face detection, and in the database management of image. Therefore, the aim of our paper is to apply Red
Green Blue (
Methods:
The morphological operations are performed in the face region to a number of pixels as the proposed parameter
to check either an input image contains face region or not. Canny edge detection is also used to show the boundaries of a
candidate face region, in the end, the face can be shown detected by using bounding box around the face.
Results:
The reliability model has also been proposed for detecting the faces in single and multiple images. The results of
the experiments reflect that the algorithm been proposed performs very well in each model for detecting the faces in single
and multiple images and the reliability model provides the best fit by analyzing the precision and accuracy. Moreover
Discussion:
The calculated results show that HSV model works best for single faced images whereas YCbCr and TSL
models work best for multiple faced images. Also, the evaluated results by this paper provides the better testing strategies
that helps to develop new techniques which leads to an increase in research effectiveness.
Conclusion:
The calculated value of all parameters is helpful for proving that the proposed algorithm has been performed
very well in each model for detecting the face by using a bounding box around the face in single as well as multiple
images. The precision and accuracy of all three models are analyzed through the reliability model. The comparison
calculated in this paper reflects that HSV model works best for single faced images whereas YCbCr and TSL models
work best for multiple faced images.
A Face Detection Method Based on Skin Color Features and AdaBoost Algorithm
