Digital correlation of computer-generated holograms for 3D face recognition

• Published in: Applied optics. Optical technology and biomedical optics Vol. 58; no. 34; p. G177
• Main Authors: Zhou, Haowen, Sui, Xiaomeng, Cao, Liangcai, Banerjee, Partha P
• Format: Journal Article
• Language: English
• Published: United States 01.12.2019
• Subjects: Algorithms; Biometry - methods; Face - anatomy & histology; Facial Recognition - physiology; Holography; Humans; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Imaging, Three-Dimensional - methods; Pattern Recognition, Automated
• ISSN: 2155-3165
• DOI: 10.1364/AO.58.00G177

Three-dimensional (3D) face recognition has been a crucial task in human biometric verification and identification. A digital correlation method of a computer-generated hologram (CGH) for 3D face recognition is proposed, which encodes 3D data into a 2D hologram for recognition. The 3D face models are preprocessed and compressed to into groups of feature points. The CGH templates corresponding to the 3D feature points are generated by point- and layer-oriented algorithms based on three different numerical algorithms to encode depth values into 2D holograms. A 2D digital correlation is performed between the CGH templates. It is demonstrated that the generated CGHs templates could be effectively classified based on the correlation performance metrics of discrimination ratio, peak-to-correlation plane energy, and peak-to-noise ratio. With the essence of the CGH algorithm being the conversion of 3D data to a 2D hologram, the proposed encoding and decoding method has great advantages in reducing computational efforts and potential applications in 3D face recognition, storage, and display.