FACIAL FEATURE EXTRACTION USING LOCAL BINARY PATTERN AND LOCAL TERNARY PATTERN WITH GRADIENT BASED ILLUMINATION NORMALIZATION
Swati Manhotra · International Journal of Advanced Research in Computer Science · 2017
This paper presents a novel method of facial feature extraction along with illumination normalization.To suppress the effect of illumination, a gradient based illumination normalization technique is used in the pre-processing stage.Facial features are extracted using two local feature extractors Local Binary Pattern and Local Ternary Pattern.Local Binary Pattern is a very efficient method of feature extraction which is insensitive to monotonic grayscale variations in the image.A face image is split into small blocks and LBP histograms are computed for each sub block and then concatenated into a single feature vector.Local Ternary Patterns is noise resistant 3-state version of LBP.The facial feature extraction process is performed on the two very popular face databases Extended Yale B and AR database.The feature vectors obtained from LBP and LTP are highly discriminative and useful for further recognition tasks.