A Study on the Effect of ROI Masks on Face Recognition System Using Digital Recorder

In recent years, biometrics authentication has been widely used to realize high security in airports, office buildings and so on. In public area, surveillance cameras, which are combined with a high efficient coding recorder such as MPEG2 or MPEG4 recorder, are set to take face images of pedestrians and car license plates. However, high compression for efficient recording leads to degradation of details in face and characters on car license plates. Consequently, it is important that region of interest (ROI) is detected correctly and recorded with high quality image. Although there are a number of proposals concerning the detection of face areas and license plates, the relationship between ROI masks and face recognition rate or character recognition rate is not cleared. In this work, we investigate the recognition rates for face authentication with compressed face images under limited storage size. Several kinds of ROI mask are compared, and face recognition rates with respect to ROIs are shown

[1]  Shaogang Gong,et al.  Multi-view face detection using support vector machines and eigenspace modelling , 2000, KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516).

[2]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[3]  Narendra Ahuja,et al.  Detecting Faces in Images: A Survey , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Y. Mitsukura,et al.  License plate detection system by using threshold function and improved template matching method , 2004, IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04..

[5]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[6]  Athanasios Leontaris,et al.  Region-o f-Interest Video Compression with a Composite and a Long-Term Frame , 2004 .

[7]  Shaogang Gong,et al.  Audio- and Video-based Biometric Person Authentication , 1997, Lecture Notes in Computer Science.

[8]  Jean-Philippe Thiran,et al.  Face Detection Using an SVM Trained in Eigenfaces Space , 2003, AVBPA.