An occlusion-resistant ellipse detection method by joining coelliptic arcs

Halil Ibrahim Cakir; Cihan Topal; Cuneyt Akinlar

doi:10.1007/978-3-319-46475-6_31

An occlusion-resistant ellipse detection method by joining coelliptic arcs

Halil Ibrahim Cakir^*
, Cihan Topal
, Cuneyt Akinlar

^*Bu çalışma için yazışmadan sorumlu yazar

Kutahya Dumlupinar University
Anadolu University
Visea Innovative Information Technologies

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

9 Atıf (Scopus)

Özet

In this study, we propose an ellipse detection method which gives prospering results on occlusive cases. The method starts with detection of edge segments. Then we extract elliptical arcs by computing corners and fitting ellipse to the pixels between two consecutive corners. Once the elliptical arcs are extracted, we aim to test all possible arc subsets. However, this requires exponential complexity and runtime diverges as the number of arcs increases. To accelerate the process, arc pairing strategy is deployed by using conic properties of arcs. If any pair found to be non-coelliptic, then arc combinations including that pair are eliminated. Therefore the number of possible arcs subsets is reduced and computation time is improved. In the end, ellipse fitting is applied to remaining arc combinations to decide on final ellipses. Performance of the proposed algorithm is tested on real datasets, and better results have been obtained compare to state-of-the-art algorithms.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Computer Vision - 14th European Conference, ECCV 2016, Proceedings
Editörler	Bastian Leibe, Nicu Sebe, Max Welling, Jiri Matas
Yayınlayan	Springer Verlag
Sayfalar	492-507
Sayfa sayısı	16
ISBN (Basılı)	9783319464749
DOI'lar	https://doi.org/10.1007/978-3-319-46475-6_31
Yayın durumu	Yayınlandı - 2016
Harici olarak yayınlandı	Evet
Etkinlik	14th European Conference on Computer Vision, ECCV 2016 - Amsterdam, Netherlands Süre: 8 Eki 2016 → 16 Eki 2016

Yayın serisi

Adı	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Hacim	9906 LNCS
ISSN (Basılı)	0302-9743
ISSN (Elektronik)	1611-3349

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	14th European Conference on Computer Vision, ECCV 2016
Ülke/Bölge	Netherlands
Şehir	Amsterdam
Periyot	8/10/16 → 16/10/16

Bibliyografik not

Publisher Copyright:
© Springer International Publishing AG 2016.

Finansman

This work is supported by The Scientific and Technological Research Council of Turkey (TUBITAK) and Anadolu University Commission of Scientific Research Projects (BAP) under the grant numbers 115E928 and 1505F319, respectively.

Finansörler	Finansör numarası
Anadolu University Commission of Scientific Research Projects
TUBITAK
British Association for Psychopharmacology	115E928, 1505F319
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu

Belgeye Erişim

10.1007/978-3-319-46475-6_31

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Cakir, H. I., Topal, C., & Akinlar, C. (2016). An occlusion-resistant ellipse detection method by joining coelliptic arcs. In B. Leibe, N. Sebe, M. Welling, & J. Matas (Eds.), Computer Vision - 14th European Conference, ECCV 2016, Proceedings (pp. 492-507). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Hac. 9906 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-46475-6_31

Cakir, Halil Ibrahim ; Topal, Cihan ; Akinlar, Cuneyt. / An occlusion-resistant ellipse detection method by joining coelliptic arcs. Computer Vision - 14th European Conference, ECCV 2016, Proceedings. editör / Bastian Leibe ; Nicu Sebe ; Max Welling ; Jiri Matas. Springer Verlag, 2016. pp. 492-507 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "An occlusion-resistant ellipse detection method by joining coelliptic arcs",

abstract = "In this study, we propose an ellipse detection method which gives prospering results on occlusive cases. The method starts with detection of edge segments. Then we extract elliptical arcs by computing corners and fitting ellipse to the pixels between two consecutive corners. Once the elliptical arcs are extracted, we aim to test all possible arc subsets. However, this requires exponential complexity and runtime diverges as the number of arcs increases. To accelerate the process, arc pairing strategy is deployed by using conic properties of arcs. If any pair found to be non-coelliptic, then arc combinations including that pair are eliminated. Therefore the number of possible arcs subsets is reduced and computation time is improved. In the end, ellipse fitting is applied to remaining arc combinations to decide on final ellipses. Performance of the proposed algorithm is tested on real datasets, and better results have been obtained compare to state-of-the-art algorithms.",

keywords = "Arc detection, Ellipse detection, Feature extraction, Hough transform",

author = "Cakir, \{Halil Ibrahim\} and Cihan Topal and Cuneyt Akinlar",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 14th European Conference on Computer Vision, ECCV 2016 ; Conference date: 08-10-2016 Through 16-10-2016",

year = "2016",

doi = "10.1007/978-3-319-46475-6\_31",

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isbn = "9783319464749",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Cakir, HI, Topal, C & Akinlar, C 2016, An occlusion-resistant ellipse detection method by joining coelliptic arcs. in B Leibe, N Sebe, M Welling & J Matas (eds), Computer Vision - 14th European Conference, ECCV 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), hac. 9906 LNCS, Springer Verlag, pp. 492-507, 14th European Conference on Computer Vision, ECCV 2016, Amsterdam, Netherlands, 8/10/16. https://doi.org/10.1007/978-3-319-46475-6_31

An occlusion-resistant ellipse detection method by joining coelliptic arcs. / Cakir, Halil Ibrahim; Topal, Cihan; Akinlar, Cuneyt.
Computer Vision - 14th European Conference, ECCV 2016, Proceedings. ed. / Bastian Leibe; Nicu Sebe; Max Welling; Jiri Matas. Springer Verlag, 2016. p. 492-507 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Hac. 9906 LNCS).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - An occlusion-resistant ellipse detection method by joining coelliptic arcs

AU - Cakir, Halil Ibrahim

AU - Topal, Cihan

AU - Akinlar, Cuneyt

N1 - Publisher Copyright: © Springer International Publishing AG 2016.

PY - 2016

Y1 - 2016

N2 - In this study, we propose an ellipse detection method which gives prospering results on occlusive cases. The method starts with detection of edge segments. Then we extract elliptical arcs by computing corners and fitting ellipse to the pixels between two consecutive corners. Once the elliptical arcs are extracted, we aim to test all possible arc subsets. However, this requires exponential complexity and runtime diverges as the number of arcs increases. To accelerate the process, arc pairing strategy is deployed by using conic properties of arcs. If any pair found to be non-coelliptic, then arc combinations including that pair are eliminated. Therefore the number of possible arcs subsets is reduced and computation time is improved. In the end, ellipse fitting is applied to remaining arc combinations to decide on final ellipses. Performance of the proposed algorithm is tested on real datasets, and better results have been obtained compare to state-of-the-art algorithms.

AB - In this study, we propose an ellipse detection method which gives prospering results on occlusive cases. The method starts with detection of edge segments. Then we extract elliptical arcs by computing corners and fitting ellipse to the pixels between two consecutive corners. Once the elliptical arcs are extracted, we aim to test all possible arc subsets. However, this requires exponential complexity and runtime diverges as the number of arcs increases. To accelerate the process, arc pairing strategy is deployed by using conic properties of arcs. If any pair found to be non-coelliptic, then arc combinations including that pair are eliminated. Therefore the number of possible arcs subsets is reduced and computation time is improved. In the end, ellipse fitting is applied to remaining arc combinations to decide on final ellipses. Performance of the proposed algorithm is tested on real datasets, and better results have been obtained compare to state-of-the-art algorithms.

KW - Arc detection

KW - Ellipse detection

KW - Feature extraction

KW - Hough transform

UR - https://www.scopus.com/pages/publications/84990861917

U2 - 10.1007/978-3-319-46475-6_31

DO - 10.1007/978-3-319-46475-6_31

M3 - Conference contribution

AN - SCOPUS:84990861917

SN - 9783319464749

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 492

EP - 507

BT - Computer Vision - 14th European Conference, ECCV 2016, Proceedings

A2 - Leibe, Bastian

A2 - Sebe, Nicu

A2 - Welling, Max

A2 - Matas, Jiri

PB - Springer Verlag

T2 - 14th European Conference on Computer Vision, ECCV 2016

Y2 - 8 October 2016 through 16 October 2016

ER -

Cakir HI, Topal C, Akinlar C. An occlusion-resistant ellipse detection method by joining coelliptic arcs. In Leibe B, Sebe N, Welling M, Matas J, editörler, Computer Vision - 14th European Conference, ECCV 2016, Proceedings. Springer Verlag. 2016. p. 492-507. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-46475-6_31

An occlusion-resistant ellipse detection method by joining coelliptic arcs

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Finansman

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap