Fast Face Detection Based on Skin Segmentation and Facial Features

Human face detection plays an important role in various biometric applications such as crowd surveillance, photography, human computer interaction, tracking, automatic target recognition and many security related areas. Varying illumination conditions, color variance, brightness, pose variations are major challenging problems for face detection. This paper proposes a localized approach for face detection based on skin color segmentation and facial features. Skin color segmentation approach decreases the computational complexity and increases the accuracy since the skin region is previously determined. For skin color segmentation, we have used Y CbCr color image. The advantage of using Y CbCr is to remove the illumination component that is represented by Y. This method is tested on two databases: Bao database: contains 157 images and Muct database: contains 751 images. The algorithm achieves an average accuracy of 96:73%. Comparison with Viola Jones and Face Detection using Skin Color Model methods has also been done.