Face Detection in Single and Multiple Images Using Different Skin Color Models

Introduction: Face Detection is used in many different steams like video conferencing, human-computer interface, face detection, and in the database management of image. Therefore, the aim of our paper is to apply Red Green Blue (RGB)and Hue Saturation Value HSV color models in detecting the single, including multiple images of any face. Each color model HSV YCbCr andTSL are individually performed with the RGB color model to detect from the single and multiple images, the region of the face. 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 a 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 a 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, YCbCr and TSL color models are observed to be outperformed than the existing HSV color model in the environment of multiple images. Discussion: The calculated results show that the HSV model works best for single-faced images, whereas YCbCr and TSL models work best for multiple faced images. In addition, the evaluated results by this paper provide better testing strategies that help to develop new techniques, which lead to an increase in research effectiveness. Conclusion: The calculated value of all parameters helps prove 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 the HSV model works best for single-faced images, whereas YCbCr and TSL models work best for multiple faced images. © 2021 Bentham Science Publishers.