Automatic eye localization; multi-block LBP vs. Pyramidal LBP three-levels image decomposition for eye visual appearance description

Abstract

This manuscript presents the performance evaluation of our algorithm that precisely finds human eyes in still gray-scale images and describes the state of the founded eye. This algorithm has been evaluated considering two descriptors - Pyramid transform domain (PLBP) and Multi-Block Histogram LBP (BHLBP), which are extended versions of the Local Binary Pattern descriptor (LBP). For the classification stage, two types of supervised learning techniques have also been evaluated, Support Vector Machine (SVM) and Multilayer Perceptron (MLP). The proposed method is assessed on the Face Recognition Grand Challenge (BioID) and (CAS-PEAL-R1) databases, and experimental results demonstrate improved performance than some state-of-the-art eye detection approaches.