Tuning of conic parameters using Tikhonov regularization and L-Curve simulation
Sintonización de los parámetros de una cónica utilizando regularización Tikhonov y simulación L-Curva
DOI:
https://doi.org/10.15446/dyna.v86n210.75996Palabras clave:
segmentation, optimization, parameter estimation (en)segmentación, optimización, estimación de parámetros (es)
Descargas
In this article, a method to infer the parameters of a conic given a set of rectangular coordinates that belong to the geometric entity is shown. The methodology consists of solving a Tikhonov regulation problem where the unregulated term introduces the non-linear nature of the conical body and the regulated the restriction associated to the discriminant of the quadratic equation, then the solution is computed minimizing the resulting cost function where the Regularization parameter is tuned using the L-Curve technique. The model was validated with synthetic and real data from digital images, as well as subject to comparison against other state of the art alternatives. The results show that the method is robust against atypical values and the phenomenon of occlusion present in the data.
Referencias
Barreto, J.P. and Araujo, H., Geometric properties of central catadioptric line images and their application in calibration. IEEE Computer Society 27, pp. 1327-1333, 2005. DOI: 10.1109/TPAMI.2005.163
Junli, L., Miaohua, Z., Ding, L., Xianju, Z., Ode, O.J., Kexin, Z., Zhan, L. and Han, L., Robust ellipse fitting based on sparse combination of data points. IEEE Computer Society 22, pp. 2207-2218, 2013.10.1109/TIP.2013.2246518
Gómez-de Castro, A.I., Orbits in the solar system. Kepler’s Laws, conics, orbital motion. In: Astronomy Workshop, Vol. 3, Universidad Complutense de Madrid, España, s.a.
Richard, H. and Andrew, Z., Multiple view geometry in computer vision, Cambrigde University Press. United States, 2000.
Zhengyou, Z., Parameter estimation techniques: a tutorial with application to conic fitting. Image and Vision Computing, Elservier, 15, pp. 59-76, 1997. DOI: 10.1016/S0262-8856(96)01112-2
Andrew, F. and Robert B.F., A buyer's guide to conic fitting. British Machine Vision Conference. Birmingham, U.K., 1995.
Andrew, F., Pilu, M. and Fisher, R., Direct least-square fitting of Ellipses. International Conference on Pattern Recognition. Vienna, Austria, 1996.
Junli, L., Miaohua, Z., Ding, L., Xianju, Z., Ode, O. J., Kexin, Z., Zhan, L. and Han, L., A comparison of ellipse fitting methods and implications for multiple-view geometry estimation. Digital Image Computing Techniques and Applications. IEEE. 2012. DOI: 10.1109/DICTA.2012.6411722
Paul, L.R., A note on the least squares fitting of ellipses., Elservier, 14, pp. 799-808, 1993. DOI: 10.1016/0167-8655(93)90062-I
Andrew, W.F., Maurizio, P. and Robert, B.F. Direct least square fitting of ellipses., IEEE, 21, pp. 476-480, 2005. DOI: 10.1109/34.765658
Yuanpeng, L. and Xiaoyan, D., Constrained least squares fitting of ellipse. Computational Intelligence and Software Engineering. IEEE. 2010. DOI: 10.1109/CISE.2010.5676736
Halir, R. and Flusser, J., Numerically stable direct least squares fitting of ellipses. In: Proc Sixth Int Conf Comp Graph Visual, 1998. DOI: 10.1.1.1.7559
Phillips, P.J., Wechsler, H., Huang, J. and Rauss, P.J., The FERET database and evaluation procedure for face-recognition algorithms. Image and vision computing, 16, pp. 295-306, 1998. DOI: 10.1016/S0262-8856(97)00070-X
Oliver, Z., Markus, M. and Wolfang., H., How good is my test data? Introducing safety analysis for computer vision, International Journal of Computer Vision, 125(1-3), pp. pp 95-109, 2017. DOI: 10.1007/s11263-017-1020-z
Bao, P., Zhang, L. and Wu, X., Canny edge detection enhancement by scale multiplication. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27, pp. 1485-1490, 2005. DOI: 10.1109/TPAMI.2005.173
Jin-Yu, Z., Yan, C. and Xian-Xiang, H., Edge detection of images based on improved Sobel operator and genetic algorithms. In: Image Analysis and Signal Processing. IASP. International Conference on, IEEE, pp. 31-35, 2009. DOI: 10.1109/IASP.2009.5054605
Rong, W., Li, Z., Zhang, W. and Sun, L., An improved CANNY edge detection algorithm. In: Mechatronics and Automation (ICMA). IEEE International Conference on, IEEE, pp. 577-582, 2014. DOI: 10.1109/ICMA.2014.6885761
Ogawa, K., Ito, Y. and Nakana, K., Efficient Canny edge detection using a GPU. In: Networking and Computing (ICNC), First International Conference on. IEEE, pp. 279-280, 2010. DOI: 10.1109/IC-NC.2010.13
Meijster, A. and Wilkinson, M.H., A comparison of algorithms for connected set openings and closings. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24, pp. 484-494, 2002. DOI: 10.1109/34.993556
Hartley, R. and Zisserman, A., Multiple view geometry in computer vision. Cambridge University press, USA, 2003.
Hansen, P.C., Computational inverse problems in electrocardiology, WIT press, Southampton, England, 2001.
Steger, C., Ulrich, M. and Wiedemann, C., Machine vision algorithms and applications. John Wiley & Sons, USA, 2018.
Hansen, P.C. and O’Leary, D.P., The use of the L-curve in the regularization of discrete ill-posed problems. SIAM Journal on Scientific Computing, 14, pp. 1487-1503, 1993. DOI: 10.1137/0914086
Chong, E.K., Zak, S.H., An introduction to optimization. John Wiley & Sons, USA, 2013.
Wong, C.Y., Lin, S.C.F., Ren, T.R. and Kwok, N.M., A survey on ellipse detection methods. In Industrial Electronics (ISIE), 2012 IEEE International Symposium on. pp. 1105-1110, 2013. DOI: 10.1109/ISIE.2012.6237243
Guil, N. and Zapata, E.L., Lower order circle and ellipse Hough transform. Pattern Recognition, 30(10), pp. 1729-1744, 1997. DOI: 10.1016/S0031-3203(96)00191-4
Maini, E.S., Enhanced direct least square fitting of ellipses. International Journal of Pattern Recognition and Artificial Intelligence, 20(06), pp. 939-953, 2006. DOI: 10.1142/S021800140600506X
Cómo citar
IEEE
ACM
ACS
APA
ABNT
Chicago
Harvard
MLA
Turabian
Vancouver
Descargar cita
CrossRef Cited-by
1. Xuandong Lu, Yunhui Su, Jinsong Yang, Tiantian Wang. (2025). Sparse load identification based on multi-level substructure condensation and response reconstruction. Structures, 80, p.109763. https://doi.org/10.1016/j.istruc.2025.109763.
Dimensions
PlumX
Visitas a la página del resumen del artículo
Descargas
Licencia
Derechos de autor 2019 DYNA

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
El autor o autores de un artículo aceptado para publicación en cualquiera de las revistas editadas por la facultad de Minas cederán la totalidad de los derechos patrimoniales a la Universidad Nacional de Colombia de manera gratuita, dentro de los cuáles se incluyen: el derecho a editar, publicar, reproducir y distribuir tanto en medios impresos como digitales, además de incluir en artículo en índices internacionales y/o bases de datos, de igual manera, se faculta a la editorial para utilizar las imágenes, tablas y/o cualquier material gráfico presentado en el artículo para el diseño de carátulas o posters de la misma revista.




