Enhancement of face recognition using modified linear binary patterns

• Main Author: Wang, Roger Zhiming.
• Other Authors: Teoh Eam Khwang
• Format: Final Year Project
• Language: English
• Published: 2011
• Subjects: DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
• Online Access: http://hdl.handle.net/10356/45785
• Institution: Nanyang Technological University

Automatic face analysis which includes, e.g., face detection, face recognition and facial expression recognition has become a very active topic in computer vision research [1], due to its various wide potential applications in public security, financial security, entertainment, intelligent human-computer interaction, etc. A key issue in face analysis is finding efficient descriptors for face appearance. Different holistic methods such as Principal Component Analysis (PCA) [2], Linear Discriminant Analysis (LDA) [3] and 2-D PCA [4] have been studied widely but lately local descriptors have gained popularity due to their robustness to challenges such as pose and illumination changes. The main focus of this project is to develop a system using modified Local Binary Pattern (LBP) to improve on face recognition. Firstly, pre-processing of database is to ensure that images are consistence throughout training and testing process. Pre-processing procedures include, decompressing of database, extracting of eye coordinates automatically or manually for accurate cropping of faces and normalisation. Precise cropping of face will ensure important information of faces is all included in the desired image.