The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Local Binary Patterns as an Image Preprocessing for Face Authentication
Open accessAbstract
One of the major problem in face authentication systems is to deal with variations in illumination. In a realistic scenario, it is very likely that the lighting conditions of the probe image does not correspond to those of the gallery image, hence there is a need to handle such variations. In this work, we present a new preprocessing algorithm based on local binary patterns (LBP): a texture representation is derived from the input face image before being forwarded to the classifier. The efficiency of the proposed approach is empirically demonstrated using both an appearance-based (LDA) and a feature-based (HMM) face authentication systems on two databases: BANCA and XM2VTS (with its darkened set). Conducted experiments show a significant improvement in terms of verification error rates and compare to results obtained with state-of-the-art preprocessing techniques
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
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
Ojala, T., Pietikainen, M., & Maenpaa, T. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2002.1017623 · Cited by 15,398
A comparative study of texture measures with classification based on featured distributions
Ojala, T., Pietikäinen, M., & Harwood, D. (1996) · Pattern Recognition · doi:10.1016/0031-3203(95)00067-4 · Cited by 6,882
Face Recognition with Local Binary Patterns
Ahonen, T., Hadid, A., & Pietikäinen, M. (2004) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-24670-1_36 · Cited by 2,462
Cited by
Local Binary Patterns and Its Application to Facial Image Analysis: A Survey
Huang, D., Shan, C., Ardabilian, M., Wang, Y., & Chen, L. (2011) · IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) · doi:10.1109/tsmcc.2011.2118750 · Cited by 905
Zhu, C., Zhou, H., Wang, R., & Guo, J. (2010) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2010.2046330 · Cited by 403
On the Use of SIFT Features for Face Authentication
Bicego, M., Lagorio, A., Grosso, E., & Tistarelli, M. (2006) · 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06) · doi:10.1109/cvprw.2006.149 · Cited by 371
Metadata
- Authors
- Heusch, G., Rodriguez, Y., & Marcel, S.
- Venue
- 7th International Conference on Automatic Face and Gesture Recognition (FGR06)
- Publisher
- IEEE
- Published
- 2006-04-28
- Pages
- 9-14
- ISSN
- 1541-5058 (ISSN-L)
- OpenAlex
- W2169200946
- Cited by
- 190
- References
- 3
- FWCI
- 16.12
- Type
- conference paper
- Language
- en
- Open access
- green
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: Local Binary Patterns as an Image Preprocessing for Face Authentication. https://app.cochat.ai/papers/10.1109/fgr.2006.72
- The paper
- Heusch, G., Rodriguez, Y., & Marcel, S. (2006). Local Binary Patterns as an Image Preprocessing for Face Authentication. 7th International Conference on Automatic Face and Gesture Recognition (FGR06). https://doi.org/10.1109/fgr.2006.72
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.