A study on face detection in images

Abstract

Face detection has been one of the most active research topics in computer vision over the past decade. Viola-Jones face locator has accepted an extraordinary consideration, and has turned into the defacto standard of face identification approaches. In this project, we have used the Haar-like features to detect faces. Only the frontal faces can be detected. The face detection is done in three phases with the algorithm specified by Paul Viola and Michael J. Jones . We get some of non- faces which are classified as faces along with the faces. We tried to reduce those non-faces from the image and keep only faces using two algorithms. The first algorithm is based on observation method of the errors and removing the non faces based on a certain threshold . The second method detect the upper body and then keep the faces which are present in the upper body and discard the non faces which are not present inside the upper body region. By using the two algorithms, we tried to minimize the non-faces in the algorithm . We have taken real life examples and simulated the algorithms in MATLAB successfully.