TY - GEN
T1 - Are Haar-like Rectangular Features for Biometric Recognition Reducible?
AU - Nasrollahi, Kamal
AU - Moeslund, Thomas B.
PY - 2013
Y1 - 2013
N2 - Biometric recognition is still a very difficult task in real-world scenarios wherein unforeseen changes in degradations factors like noise, occlusion, blurriness and illumination can drastically affect the extracted features from the biometric signals. Very recently Haar-like rectangular features which have usually been used for object detection were introduced for biometric recognition resulting in systems that are robust against most of the mentioned degradations [9]. The problem with these features is that one can define many different such features for a given biometric signal and it is not clear whether all of these features are required for the actual recognition or not. This is exactly what we are dealing with in this paper: How can an initial set of Haar-like rectangular features, that have been used for biometric recognition, be reduced to a set of most influential features? This paper proposes total sensitivity analysis about the mean for this purpose for two different biometric traits, iris and face. Experimental results on multiple public databases show the superiority of the proposed system, using the found influential features, compared to state-of-the-art biometric recognition systems.
AB - Biometric recognition is still a very difficult task in real-world scenarios wherein unforeseen changes in degradations factors like noise, occlusion, blurriness and illumination can drastically affect the extracted features from the biometric signals. Very recently Haar-like rectangular features which have usually been used for object detection were introduced for biometric recognition resulting in systems that are robust against most of the mentioned degradations [9]. The problem with these features is that one can define many different such features for a given biometric signal and it is not clear whether all of these features are required for the actual recognition or not. This is exactly what we are dealing with in this paper: How can an initial set of Haar-like rectangular features, that have been used for biometric recognition, be reduced to a set of most influential features? This paper proposes total sensitivity analysis about the mean for this purpose for two different biometric traits, iris and face. Experimental results on multiple public databases show the superiority of the proposed system, using the found influential features, compared to state-of-the-art biometric recognition systems.
KW - Haar-like rectangular features
KW - Biometric recognition
U2 - 10.1007/978-3-642-41827-3_42
DO - 10.1007/978-3-642-41827-3_42
M3 - Article in proceeding
SN - 978-3-642-41826-6
VL - 8259
T3 - Lecture Notes in Computer Science
SP - 334
EP - 341
BT - Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
A2 - Ruiz-Shulcloper, José
A2 - Sanniti di Baja, Gabriella
PB - Springer Publishing Company
CY - Springer Berlin Heidelberg
T2 - 18th Iberoamerican Congress on Pattern Recognition
Y2 - 20 November 2013 through 23 November 2013
ER -