The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Shape-based hand recognition
Abstract
The problem of person recognition and verification based on their hand images has been addressed. The system is based on the images of the right hands of the subjects, captured by a flatbed scanner in an unconstrained pose at 45 dpi. In a pre-processing stage of the algorithm, the silhouettes of hand images are registered to a fixed pose, which involves both rotation and translation of the hand and, separately, of the individual fingers. Two feature sets have been comparatively assessed, Hausdorff distance of the hand contours and independent component features of the hand silhouette images. Both the classification and the verification performances are found to be very satisfactory as it was shown that, at least for groups of about five hundred subjects, hand-based recognition is a viable secure access control scheme.
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Cites
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Cited by
A review of biometric technology along with trends and prospects
Unar, J. A., Seng, W. C., & Abbasi, A. (2014) · Pattern Recognition · doi:10.1016/j.patcog.2014.01.016 · Cited by 404
A survey of biometric technology based on hand shape
Duta, N. (2009) · Pattern Recognition · doi:10.1016/j.patcog.2009.02.007 · Cited by 165
Metadata
- Authors
- Yoruk, E., Konukoglu, E., Sankur, B., & Darbon, J.
- Venue
- IEEE Transactions on Image Processing
- Published
- 2006-07
- Volume
- 15
- Issue
- 7
- Pages
- 1803-1815
- ISSN
- 1057-7149 (ISSN-L)
- OpenAlex
- W2122393977
- Cited by
- 305
- References
- 18
- FWCI
- 25.22
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
