ICP registration using principal line and orientation features for palmprint alignment

Image alignment is a crucial step for palmprint recognition. Current key point based palmprint pre-processing methods, however, can only provide coarse alignment. The rotation of extracted region of interest (ROI) often causes the failure of genuine matching. To solve this problem, in this paper we propose to use iterative closest point (ICP) algorithm for palmprint alignment before matching of features. Using both the palm line and orientation features extracted by high order steerable filters, the proposed method has fast convergence speed and high registration accuracy, which result in greatly improved verification accuracy. Experimental results on Hong Kong PolyU palmprint database demonstrate the effectiveness of the proposed method.

[1]  Tieniu Tan,et al.  Ordinal palmprint represention for personal identification [represention read representation] , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[2]  Mathews Jacob,et al.  Design of steerable filters for feature detection using canny-like criteria , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  David Zhang,et al.  Principal line based ICP alignment for palmprint verification , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[4]  David Zhang,et al.  Palmprint verification based on robust line orientation code , 2007, Pattern Recognit..

[5]  Edward H. Adelson,et al.  The Design and Use of Steerable Filters , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  David Zhang,et al.  Online Palmprint Identification , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  David Zhang,et al.  On-Line Palmprint Identification , 2005 .

[8]  David Zhang,et al.  Competitive coding scheme for palmprint verification , 2004, ICPR 2004.

[9]  Sang Wook Lee,et al.  ICP Registration Using Invariant Features , 2002, IEEE Trans. Pattern Anal. Mach. Intell..