Contactless Print Capture

New Directions in Contact Free Hand Recognition/h1> by Xiaoqian Jiang, Wanhong Xu, Latanya Sweeney, Yiheng Li, Ralph Gross, and Daniel Yurovsky.

Abstract

The ability to quickly compute hand geometry measurements from a freely posed hand offers advantages to biometric identification systems. While hand geometry systems are not new, typical measurements of lengths and widths of fingers and palms require rigid placement of the hand against pegs. Slight deviations in hand position, finger stretch or pressure can yield different measurements. This paper offers novel approaches to computing hand geometry measurements from frontal views of freely posed hands. These approaches offer advantages in hygiene, comfort and reliability. Our algorithms segment the hand from a known background under spot lights and locate feature points along the fingers and wrists. Given a database of 54 hand images, with three different images of the same hand of each subject, our approach uniquely identified a previously unseen hand with an overall accuracy of 92%.

Keywords: image processing, machine learning, fingerprints, palm prints, hand geometry, contactless capture, friction ridge capture

Citation:
Xiaoqian Jiang, Wanhong Xu,
Latanya Sweeney, Yiheng Li, Ralph Gross, and Daniel Yurovsky. New Directions in Contact Free Hand Recognition. IEEE International Conference on Image Processing (ICIP). San Antonio, Texas, September 2007. (PDF).

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