TY - GEN
T1 - Face recognition based on near-infrared light using mobile phone
AU - Han, Song Yi
AU - Park, Hyun Ae
AU - Cho, Dal Ho
AU - Park, Kang Ryoung
AU - Lee, Sangyoun
PY - 2007
Y1 - 2007
N2 - Recently, many companies have attempted to adopt biomeric technology in their mobile phones. In this paper, we propose a new NIR (NearInfra-Red) lighting face recognition method for mobile phones by using megapixel camera image. This paper presents four advantages and contributions over previous research. First, we propose a new eye detection method for face localization for mobile phones based on corneal specular reflections. To detect these SRs (Specular Reflections) (even for users with glasses), we propose successive On/Off activation of the dual NIR illuminators of mobile phone. Second, because the face image is captured by the NIR illuminator, the nose area can be highly saturated, which can degrade face recognition accuracy. To overcome this problem, we use a simple logarithmic image enhancement method, which is suitable for mobile phones with low processing power. Third, considering the low processing speed of mobile phones, we adopt integer-based PCA (Principal Component Analysis) method for face recognition excluding floating-point operation. Fouth, by comparing the recognition performance using the integer-based PCA to those using LDA (Linear Discriminant Analysis) and ICA (Independent Component Analysis) methods, we could know that the integer-based PCA showed better performance apt for mobile phone with NIR image.
AB - Recently, many companies have attempted to adopt biomeric technology in their mobile phones. In this paper, we propose a new NIR (NearInfra-Red) lighting face recognition method for mobile phones by using megapixel camera image. This paper presents four advantages and contributions over previous research. First, we propose a new eye detection method for face localization for mobile phones based on corneal specular reflections. To detect these SRs (Specular Reflections) (even for users with glasses), we propose successive On/Off activation of the dual NIR illuminators of mobile phone. Second, because the face image is captured by the NIR illuminator, the nose area can be highly saturated, which can degrade face recognition accuracy. To overcome this problem, we use a simple logarithmic image enhancement method, which is suitable for mobile phones with low processing power. Third, considering the low processing speed of mobile phones, we adopt integer-based PCA (Principal Component Analysis) method for face recognition excluding floating-point operation. Fouth, by comparing the recognition performance using the integer-based PCA to those using LDA (Linear Discriminant Analysis) and ICA (Independent Component Analysis) methods, we could know that the integer-based PCA showed better performance apt for mobile phone with NIR image.
UR - http://www.scopus.com/inward/record.url?scp=38049066476&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-71629-7_50
DO - 10.1007/978-3-540-71629-7_50
M3 - Conference contribution
AN - SCOPUS:38049066476
SN - 9783540715900
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 440
EP - 448
BT - Adaptive and Natural Computing Algorithms - 8th International Conference, ICANNGA 2007, Proceedings
PB - Springer Verlag
T2 - 8th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2007
Y2 - 11 April 2007 through 14 April 2007
ER -