Efficient face recognition in video by bit planes slicing

Abstract: Problem statement: Video-based face recognition must be able to overcome the imaging interference such as pose and illumination. Approach: A model is designed to study for face recognition based on video sequence and also test image. In training stage, single frontal image is taken as a input to the recognition system. A new virtual image is generated using bit plane feature fusion to effectively reduce the sensitivity to illumination variances. A Self-PCA is performed to get each set of Eigen faces and to get projected image. In recognition stage, automatic face detection scheme is first applied to the video sequences. Frames are extracted from the video and virtual frame is created. Each bit plane of test face is extracted and then the feature fusion face is constructed, followed by the projection and reconstruction using each set of the corresponding Eigen faces. Results: This algorithm is compared with conventional PCA algorithm. The minimum error of reconstruction is calculated. If error is less than a threshold value, then it recognizes the face from the database. Conclusion: Bit plane slicing mechanism is applied in video based face recognition. Experimental results shows that its far more superior than conventional method under various pose and illumination condition