Face Detection Using Fusion of LBP and AdaBoost
Arezou Chehrehgosha, Mehran Emadi · Journal of Soft Computing and Applications · 2016
The human face is a dynamic object which a high degree of variability exists in its appearance. This makes the face detection to be considered as the first and most essential step in face recognition systems. The aim of the face detection is the segmentation of the face. There are several problems in face detection, including state switching, changing light intensity, face covering, etc. To solve these problems, the present study utilizes an advanced algorithm based on the LBP method and a structured Adaboost algorithm using the FERET database. The output will be attained by entering the normalized data into a three-layer LBP Adaboost fed with the data from data bases. It was found that the method has the acceptable detection accuracy of 75%, detection feature of 72% and sensitivity of 77% , and the final detection result of the human face is up to 98% possible.