Title :
Principal axis and crease detection for slap fingerprint segmentation
Author :
Zhang, Yong-Liang ; Li, Yan-Miao ; Wu, Hong-Tao ; Huang, Ya-ping ; Xiao, Gang ; Gao, Fei
Author_Institution :
Inst. of Graphical & Image Process., Zhejiang Univ. of Technol., Hangzhou, China
Abstract :
In slap fingerprint segmentation, crease is the most difficult edge to correctly detect. In this paper, we present a novel yet simple and accurate algorithm for the principal axis and crease detection. Firstly, the principal axis of each foreground region is detected using the minimal rotational inertia; Secondly, the crease detection is done based on cost function minimization. This algorithm has been incorporated in a slap fingerprint segmentation scheme, previously developed by the authors, producing successful results.
Keywords :
fingerprint identification; image segmentation; minimisation; object detection; Iminimal rotational inertia; cost function minimization; crease detection; principal axis; slap fingerprint segmentation; Algorithm design and analysis; Cost function; Fingerprint recognition; Frequency domain analysis; Image edge detection; Image segmentation; Minimization; cost function; crease; rotational inertia; segmentation; slap fingerprint;
Conference_Titel :
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-7992-4
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2010.5654266