P. Hough and I. Int, Conf. High Energy Accelerators and Instrumentation. Machine analysis of bubble chamber pictures, pp.554-556, 1959.

A. Rosenfeld, Picture Processing by Computer, ACM Computing Surveys, vol.1, issue.3, pp.147-176, 1969.
DOI : 10.1145/356551.356554

J. Illingworth and J. Kittler, A survey of the Hough transform, Comput. Vis. Graph. Image Process, vol.4488, issue.1, pp.87-11610, 1988.

V. Leavers, Which Hough transform? CVGIP: Image Underst, pp.250-264, 1993.

P. Mukhopadhyay and . Chaudhuri, A survey of Hough Transform, Pattern Recognition, vol.48, issue.3, pp.993-1010, 2015.
DOI : 10.1016/j.patcog.2014.08.027

R. Duda and P. Hart, Use of the Hough transformation to detect lines and curves in pictures, Communications of the ACM, vol.15, issue.1, pp.11-1510, 1972.
DOI : 10.1145/361237.361242

N. Bennett, N. Burridge, and . Salto, A method to detect and characterize ellipses using the Hough transform, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.21, issue.7, pp.652-65710, 1999.
DOI : 10.1109/34.777377

J. Song and . Lyu, A Hough transform based line recognition method utilizing both parameter space and image space, Pattern Recognition, vol.38, issue.4, pp.539-552, 2005.
DOI : 10.1016/j.patcog.2004.09.003

D. Walsh and A. Raftery, Accurate and efficient curve detection in images: the importance sampling Hough transform, Pattern Recognition, vol.35, issue.7, pp.1421-143110, 2002.
DOI : 10.1016/S0031-3203(01)00114-5

D. Ballard, Generalizing the Hough transform to detect arbitrary shapes, Pattern Recognition, vol.13, issue.2, pp.111-12210, 1981.
DOI : 10.1016/0031-3203(81)90009-1

B. Leibe, . Leonardis, and . Schiele, An Implicit Shape Model for Combined Object Categorization and Segmentation, Toward Category-Level Object Recognition. Lecture Notes in Computer Science, pp.508-524, 2006.
DOI : 10.1007/11957959_26

V. Ferrari, C. Jurie, and . Schmid, From Images to Shape Models for Object Detection, International Journal of Computer Vision, vol.26, issue.5, pp.284-303, 2010.
DOI : 10.1007/s11263-009-0270-9
URL : https://hal.archives-ouvertes.fr/inria-00548643

R. Stephens, Probabilistic approach to the Hough transform, Image and Vision Computing, vol.9, issue.1, pp.66-7110, 1991.
DOI : 10.1016/0262-8856(91)90051-P

N. Kiryati, Y. Eldar, and . Bruckstein, A probabilistic Hough transform, Pattern Recognition, vol.24, issue.4, pp.303-31610, 1991.
DOI : 10.1016/0031-3203(91)90073-E

J. Matas, C. Galambos, and J. Kittler, Robust Detection of Lines Using the Progressive Probabilistic Hough Transform, Computer Vision and Image Understanding, vol.78, issue.1, pp.119-137, 2000.
DOI : 10.1006/cviu.1999.0831

L. Xu, P. Oja, and . Kultanen, A new curve detection method: Randomized Hough transform (RHT), Pattern Recognition Letters, vol.11, issue.5, pp.331-33810, 1990.
DOI : 10.1016/0167-8655(90)90042-Z

L. Xu, A unified perspective and new results on RHT computing, mixture based learning, and multi-learner based problem solving, Pattern Recognition, vol.40, issue.8, pp.2129-2153, 2007.
DOI : 10.1016/j.patcog.2006.12.016

H. Kälviäinen, . Hirvonen, E. Xu, and . Oja, Probabilistic and non-probabilistic Hough transforms: overview and comparisons, Image and Vision Computing, vol.13, issue.4, pp.239-25210, 1995.
DOI : 10.1016/0262-8856(95)99713-B

N. Kiryati and . Kälviäinen, Randomized or probabilistic Hough transform: unified performance evaluation, Pattern Recognition Letters, vol.21, issue.13-14, pp.13-14, 2000.
DOI : 10.1016/S0167-8655(00)00077-5
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.9969

F. O-'gorman and M. Clowes, Finding picture edges through collinearity of feature points, IEEE Trans. Comput. C, vol.25, issue.4, pp.449-456, 1976.

S. Shapiro, Feature space transforms for curve detection, Pattern Recognition, vol.10, issue.3, pp.129-14310, 1978.
DOI : 10.1016/0031-3203(78)90022-5

S. Karabernou and F. Terranti, Real-time FPGA implementation of Hough Transform using gradient and CORDIC algorithm, Image and Vision Computing, vol.23, issue.11, pp.1009-1017, 2005.
DOI : 10.1016/j.imavis.2005.07.004
URL : https://hal.archives-ouvertes.fr/hal-00783051

C. Galambos, J. Kittler, and . Matas, Gradient based progressive probabilistic Hough transform, IEE Proceedings - Vision, Image, and Signal Processing, vol.148, issue.3, pp.158-165, 2001.
DOI : 10.1049/ip-vis:20010354

R. Valenti and T. Gevers, Accurate eye center location and tracking using isophote curvature, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008.
DOI : 10.1109/CVPR.2008.4587529
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.175.850

Z. Yao and W. Yi, Curvature aided Hough transform for circle detection, Expert Systems with Applications, vol.51, pp.26-33, 2016.
DOI : 10.1016/j.eswa.2015.12.019

A. Kesidis and N. Papamarkos, On the gray-scale inverse Hough transform, Image and Vision Computing, vol.18, issue.8, pp.607-61810, 2000.
DOI : 10.1016/S0262-8856(99)00067-0

T. Atherton and D. Kerbyson, Size invariant circle detection, Image and Vision Computing, vol.17, issue.11, pp.795-80310, 1999.
DOI : 10.1016/S0262-8856(98)00160-7
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.24.3310

R. Dahyot and . Hough, Statistical Hough Transform, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.8, pp.1502-1509288, 2008.
DOI : 10.1109/TPAMI.2008.288

D. Marr and E. Hildreth, Theory of Edge Detection, Proceedings of the Royal Society B: Biological Sciences, vol.207, issue.1167, pp.187-2170020, 1167.
DOI : 10.1098/rspb.1980.0020

. Bkp-horn and . Schunck, Determining optical flow, 1980.

D. Lowe, Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, vol.60, issue.2, pp.91-110, 2004.
DOI : 10.1023/B:VISI.0000029664.99615.94
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.4931

T. Lindeberg, Edge detection and ridge detection with automatic scale selection, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.117-15610, 1998.
DOI : 10.1109/CVPR.1996.517113
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.4053

J. Koenderink, The structure of images, Biological Cybernetics, vol.27, issue.269, pp.363-37010, 1984.
DOI : 10.1007/BF00336961

R. Bmt-haar, Front-end vision and multi-scale image analysis, Computational Imaging and Vision, 2003.

A. Witkin, IJCAI'83. Scale-space filtering, Proceedings of the Eighth International Joint Conference on Artificial Intelligence, pp.1019-1022, 1983.

L. Florack, . Ter-haar-romeny, J. Viergever, and . Koenderink, The Gaussian scale-space paradigm and the multiscale local jet, International Journal of Computer Vision, vol.24, issue.1, pp.61-7510, 1996.
DOI : 10.1007/BF00126140

T. Lindeberg, Feature detection with automatic scale selection, International Journal of Computer Vision, vol.30, issue.2, pp.79-11610, 1998.
DOI : 10.1023/A:1008045108935

. Hk-yuen, . Princen, J. Illingworth, and . Kittler, Comparative study of Hough Transform methods for circle finding, Image and Vision Computing, vol.8, issue.1, pp.71-7710, 1990.
DOI : 10.1016/0262-8856(90)90059-E

R. Chan, New parallel Hough transform for circles, IEE Proceedings E Computers and Digital Techniques, vol.138, issue.5, pp.335-344, 1991.
DOI : 10.1049/ip-e.1991.0046

D. Ioannou, . Huda, and . Laine, Circle recognition through a 2D Hough Transform and radius histogramming, Image and Vision Computing, vol.17, issue.1, pp.15-2610, 1999.
DOI : 10.1016/S0262-8856(98)00090-0
URL : http://ufdc.ufl.edu/LS00000719/00002

I. Young and . Van-vliet, Recursive implementation of the Gaussian filter. Signal Process, pp.139-15110, 1995.

C. Kimme, J. Ballard, and . Sklansky, Finding circles by an array of accumulators, Communications of the ACM, vol.18, issue.2, pp.120-12210, 1975.
DOI : 10.1145/360666.360677

S. Fortune, SCG '86. A sweepline algorithm for Voronoi diagrams, Proceedings of the Second Annual Symposium on Computational Geometry, pp.313-322, 1986.

A. Manzanera, AMINA'12) Dense Hough transforms on gray level images using multi-scale derivatives, Proceedings of the Sixth International Workshop on Medical and Healthcare applications, pp.2012-55
DOI : 10.1186/s13640-016-0149-y
URL : http://doi.org/10.1186/s13640-016-0149-y

J. Gall, . Yao, . Razavi, V. Van-gool, and . Lempitsky, Hough Forests for Object Detection, Tracking, and Action Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.11, pp.2188-220270, 2011.
DOI : 10.1109/TPAMI.2011.70
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.204.6049

O. Barinova, P. Vs-lempitsky, and . Kohli, On Detection of Multiple Object Instances Using Hough Transforms, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.9, pp.1773-1784, 2012.
DOI : 10.1109/TPAMI.2012.79