Face Detection Methods

Human face detection plays a major role in face recognition systems and has gained much attention in recent years. Various methods were proposed to detect faces in different orientations. The aim of this paper is to introduce a comparative study of four detection methods regarding the detection rate. These methods are : SMQT Features and SNOW Classifier (SFSC) method, Efficient and Rank Deficient Face Detection (ERDFD) method, Gabor-Feature Extraction and Neural Network (GFENN) method and An efficient face candidates selector Features (EFCSF) method.The experimental results of the methods have been performed on the wild data set (FDDB) using MatLab 7.9. SFSC method achieved higher detection rate. Key-Words: Face Detection, Feature Extraction, Detection Rate, Neural Networks, Data Set, Pixel Information