TY - GEN
T1 - Contactless palmprint alignment based on intrinsic local affine-invariant feature points
AU - Phromsuthirak, Choopol
AU - Tangsuksant, Watcharin
AU - Sanpanich, Arthorn
AU - Pintavirooj, Chuchart
N1 - Publisher Copyright:
© 2014 Asia-Pacific Signal and Information Processing Ass.
PY - 2014/2/12
Y1 - 2014/2/12
N2 - A Palmprint, biométrie characteristics, was mostly found in civil and commercial applications for security system because it has more reliable and easy to capture by low resolution devices. This paper was to develop a new contactless palmprint alignment with general USB camera on tripod. The palmprint image is acquired by this camera and using intrinsic local affine-invariant key points residing on the area patches spanning between two successive fingers to align palmprint image. The key points are relative affine invariant to affine transformations so this algorithm does not need the guidance pegs in acquisition process to fix hand position to avoid the scaling, translation and rotation problems for correctly palmprint image alignment. Finally, the developed algorithm was tested by 10 left-handed palmprint images collected from different subjects. The simulation results indicate by distance map error of 1.4899 pixels.
AB - A Palmprint, biométrie characteristics, was mostly found in civil and commercial applications for security system because it has more reliable and easy to capture by low resolution devices. This paper was to develop a new contactless palmprint alignment with general USB camera on tripod. The palmprint image is acquired by this camera and using intrinsic local affine-invariant key points residing on the area patches spanning between two successive fingers to align palmprint image. The key points are relative affine invariant to affine transformations so this algorithm does not need the guidance pegs in acquisition process to fix hand position to avoid the scaling, translation and rotation problems for correctly palmprint image alignment. Finally, the developed algorithm was tested by 10 left-handed palmprint images collected from different subjects. The simulation results indicate by distance map error of 1.4899 pixels.
KW - Biometric
KW - Convex hull
KW - Otsu's thresholding
KW - Palmprint alignment
KW - Palmprint identification
UR - https://www.scopus.com/pages/publications/84949925357
U2 - 10.1109/APSIPA.2014.7041563
DO - 10.1109/APSIPA.2014.7041563
M3 - Conference contribution
AN - SCOPUS:84949925357
T3 - 2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014
BT - 2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014
Y2 - 9 December 2014 through 12 December 2014
ER -