From 0331af01ae020f812e226e510e54f857de78c28f Mon Sep 17 00:00:00 2001
From: MaximSmolskiy <mithridatus@mail.ru>
Date: Tue, 7 Jan 2025 22:24:48 +0300
Subject: [PATCH] Change article for fitEllipseDirect function

---
 doc/opencv.bib                              | 19 +++++--------------
 modules/imgproc/include/opencv2/imgproc.hpp |  2 +-
 samples/cpp/fitellipse.cpp                  |  2 +-
 3 files changed, 7 insertions(+), 16 deletions(-)

diff --git a/doc/opencv.bib b/doc/opencv.bib
index e3363a181c..f944747a7d 100644
--- a/doc/opencv.bib
+++ b/doc/opencv.bib
@@ -424,20 +424,11 @@
   publisher = {BMVA Press},
   url = {https://www.researchgate.net/profile/Robert_Fisher5/publication/2237785_A_Buyer's_Guide_to_Conic_Fitting/links/0fcfd50f59aeded518000000/A-Buyers-Guide-to-Conic-Fitting.pdf}
 }
-@article{fitzgibbon1999,
-  abstract = {This work presents a new efficient method for fitting ellipses to scattered data. Previous algorithms either fitted general conics or were computationally expensive. By minimizing the algebraic distance subject to the constraint 4ac-b<sup>2</sup>=1, the new method incorporates the ellipticity constraint into the normalization factor. The proposed method combines several advantages: It is ellipse-specific, so that even bad data will always return an ellipse. It can be solved naturally by a generalized eigensystem. It is extremely robust, efficient, and easy to implement},
-  author = {Fitzgibbon, Andrew and Pilu, Maurizio and Fisher, Robert B.},
-  doi = {10.1109/34.765658},
-  isbn = {0162-8828},
-  issn = {01628828},
-  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
-  number = {5},
-  pages = {476--480},
-  pmid = {708},
-  title = {Direct least square fitting of ellipses},
-  volume = {21},
-  year = {1999},
-  url = {https://pdfs.semanticscholar.org/090d/25f94cb021bdd3400a2f547f989a6a5e07ec.pdf}
+@inproceedings{oy1998NumericallySD,
+  title = {Numerically Stable Direct Least Squares Fitting of Ellipses},
+  author = {Radim Hal oy and Jan Flusser},
+  year = {1998},
+  url = {https://www.semanticscholar.org/paper/Numerically-Stable-Direct-Least-Squares-Fitting-of-oy-Flusser/9a8607575ba9c6016e9f3db5e52f5ed4d14d5dfd}
 }
 @article{Gallego2014ACF,
   title = {A Compact Formula for the Derivative of a 3-D Rotation in Exponential Coordinates},
diff --git a/modules/imgproc/include/opencv2/imgproc.hpp b/modules/imgproc/include/opencv2/imgproc.hpp
index bb0cab7426..90b18eebe0 100644
--- a/modules/imgproc/include/opencv2/imgproc.hpp
+++ b/modules/imgproc/include/opencv2/imgproc.hpp
@@ -4342,7 +4342,7 @@ CV_EXPORTS_W RotatedRect fitEllipseAMS( InputArray points );
 
  The function calculates the ellipse that fits a set of 2D points.
  It returns the rotated rectangle in which the ellipse is inscribed.
- The Direct least square (Direct) method by @cite Fitzgibbon1999 is used.
+ The Direct least square (Direct) method by @cite oy1998NumericallySD is used.
 
  For an ellipse, this basis set is \f$ \chi= \left(x^2, x y, y^2, x, y, 1\right) \f$,
  which is a set of six free coefficients \f$ A^T=\left\{A_{\text{xx}},A_{\text{xy}},A_{\text{yy}},A_x,A_y,A_0\right\} \f$.
diff --git a/samples/cpp/fitellipse.cpp b/samples/cpp/fitellipse.cpp
index 7d217014d5..60f72cd4ef 100644
--- a/samples/cpp/fitellipse.cpp
+++ b/samples/cpp/fitellipse.cpp
@@ -5,7 +5,7 @@
  *  contours and approximate it by ellipses using three methods.
  *  1: OpenCV's original method fitEllipse which implements Fitzgibbon 1995 method.
  *  2: The Approximate Mean Square (AMS) method fitEllipseAMS  proposed by Taubin 1991
- *  3: The Direct least square (Direct) method fitEllipseDirect proposed by Fitzgibbon1999.
+ *  3: The Direct least square (Direct) method fitEllipseDirect proposed by oy1998NumericallySD.
  *
  *  Trackbar specify threshold parameter.
  *