A real-time face detection based on skin detection and geometry features

In recent decades, researchers have been interested in face detection due to its application in computer vision and pattern recognition technologies, which themselves, commercially and academically, are so valuable. There are different approaches for face detection such as feature-based approach, appearance-based approach, template-based approach, and knowledge-based approach. The main challenges in face detection are complex backgrounds and various poses. The most proposed methods have focused on these two challenges. Another challenge is considered as various lighting conditions. The proposed method is a color-based method that uses skin color features and its performance has been proven as a fast classification method in face detection. There are different color spaces; the proposed method used YCbCr color space because it has the best result in the proper lighting conditions, RGB color space is used to increase accuracy and remove confusing objects, and also HSV color space is employed for images with unsuitable lighting conditions. Morphology operation is used to increase speed and accuracy. Such geometric features as hole, width, and height are used to determine a face. Results showed that the precision of the proposed method is 92.4%, 91%, and 93% on databases Bao, IMM, and Aberdeen, respectively. Also, the recall value of the proposed method on the Champion dataset is 94.27%.