The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Iris recognition: an emerging biometric technology
Abstract
This paper examines automated iris recognition as a biometrically based technology for personal identification and verification. The motivation for this endeavor stems from the observation that the human iris provides a particularly interesting structure on which to base a technology for noninvasive biometric assessment. In particular the biomedical literature suggests that irises are as distinct as fingerprints or patterns of retinal blood vessels. Further, since the iris is an overt body, its appearance is amenable to remote examination with the aid of a machine vision system. The body of this paper details issues in the design and operation of such systems. For the sake of illustration, extant systems are described in some amount of detail.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Laplacian pyramid as a compact image code
Burt, P., & Adelson, E. (1983) · IEEE Transactions on Communications · doi:10.1109/tcom.1983.1095851 · Cited by 6,077
Cited by
Online palmprint identification
Zhang, D., Kong, W.-K., You, J., & Wong, M. (2003) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2003.1227981 · Cited by 1,506
Personal identification based on iris texture analysis
Ma, L., Tan, T., Wang, Y., & Zhang, D. (2003) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2003.1251145 · Cited by 960
Efficient Iris Recognition by Characterizing Key Local Variations
Ma, L., Tan, T., Wang, Y., & Zhang, D. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2004.827237 · Cited by 931
Image understanding for iris biometrics: A survey
Bowyer, K. W., Hollingsworth, K., & Flynn, P. J. (2008) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2007.08.005 · Cited by 907
uWave: Accelerometer-based personalized gesture recognition and its applications
Liu, J., Wang, Z., Zhong, L., Wickramasuriya, J., & Vasudevan, V. (2009) · 2009 IEEE International Conference on Pervasive Computing and Communications · doi:10.1109/percom.2009.4912759 · Cited by 559
Metadata
- Authors
- Wildes, R. P.
- Venue
- Proceedings of the IEEE
- Published
- 1997
- Volume
- 85
- Issue
- 9
- Pages
- 1348-1363
- ISSN
- 0018-9219 (ISSN-L)
- OpenAlex
- W2171759622
- Cited by
- 2,202
- References
- 1
- FWCI
- 6.90
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Iris recognition: an emerging biometric technology. https://app.cochat.ai/papers/10.1109/5.628669
- The paper
- Wildes, R. P. (1997). Iris recognition: an emerging biometric technology. Proceedings of the IEEE. https://doi.org/10.1109/5.628669
Data sources
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.