Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 313

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Full-field strain measurement using a two-dimensional Savitzky-Golay digital differentiator in digital image correlation

Pan, Bing·2007·Optical Engineering

Abstract

Many published research works regarding digital image correlation (DIC) have been focused on the improvements of the accuracy of displacement estimation. However, the original displacement fields calculated at discrete locations using DIC are unavoidably contaminated by noises. If the strain fields are directly computed by differentiating the original displacement fields, the noises will be amplified even at a higher level, and the resulting strain fields are untrustworthy. Based on the principle of local least-square fitting using two-dimensional (2D) polynomials, a 2D Savitzky-Golay (SG) digital differentiator is deduced and used to calculate strain fields from the original displacement fields obtained by DIC. The calculation process can be easily implemented by convolving the SG digital differentiator with the estimated displacement fields. Both homogeneous and inhomogeneous deformation images are employed to verify the proposed technique. The calculated strain fields clearly demonstrate that the proposed technique is simple and effective.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1117/1.2714926

Cites

9 of 9 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 9 references

Cited by

See all 313

Metadata

Authors
Pan, B.
Venue
Optical Engineering
Published
2007-03-01
Volume
46
Issue
3
Pages
033601
ISSN
0091-3286 (ISSN-L)
OpenAlex
W2130765986
Cited by
313
References
9
FWCI
13.53
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: Full-field strain measurement using a two-dimensional Savitzky-Golay digital differentiator in digital image correlation. https://app.cochat.ai/papers/10.1117/1.2714926
The paper
Pan, B. (2007). Full-field strain measurement using a two-dimensional Savitzky-Golay digital differentiator in digital image correlation. Optical Engineering. https://doi.org/10.1117/1.2714926

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.