A hybrid approach of AdaBoost and Artificial Neural Network for detecting human faces

The human face image recognition is one of the prominent problems at present. Recognizing human faces correctly will aid some fields such as national defense and person verification. One of the most vital processing of recognizing face images is to detect human faces in the images. Some approaches have been used to detect human faces. However, they still have some limitations. In the paper, we will consider some popular methods, AdaBoost, artificial neural network (ANN) etc., for detecting human faces. Then we will propose a hybrid model of combining AdaBoost and artificial neural network to solve the process efficiently. The system which was build from the proposed model has been conducted on database CalTech. The recognition correctness is more than 96%. It shows the feasibility of the proposed model.