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LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00003320naa a2200397 4500
001oai:DiVA.org:umu-112312
003SwePub
008151205s2016 | |||||||||||000 ||eng|
0247 a https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1123122 URI
0247 a https://doi.org/10.1016/j.patcog.2015.12.0042 DOI
040 a (SwePub)umu
041 a engb eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
1001 a Hanqing, Zhangu Umeå universitet,Institutionen för fysik4 aut0 (Swepub:umu)hazh0006
2451 0a A fast and robust circle detection method using isosceles triangles sampling
264 1b Elsevier,c 2016
338 a print2 rdacarrier
520 a Circle detection using randomized sampling has been developed in recent years to reduce computational intensity. However, randomized sampling is sensitive to noise that can lead to reduced accuracy and false-positive candidates. To improve on the robustness of randomized circle detection under noisy conditions this paper presents a new methodology for circle detection based upon randomized isosceles triangles sampling. It is shown that the geometrical property of isosceles triangles provides a robust criterion to find relevant edge pixels which, in turn, offers an efficient means to estimate the centers and radii of circles. For best efficiency, the estimated results given by the sampling from individual connected components of the edge map were analyzed using a simple clustering approach. To further improve on the accuracy we applied a two-step refinement process using chords and linear error compensation with gradient information of the edge pixels. Extensive experiments using both synthetic and real images have been performed. The results are compared to leading state-of-the-art algorithms and it is shown that the proposed methodology has a number of advantages: it is efficient in finding circles with a low number of iterations, it has high rejection rate of false-positive circle candidates, and it has high robustness against noise. All this makes it adaptive and useful in many vision applications.
650 7a NATURVETENSKAPx Data- och informationsvetenskapx Datorseende och robotik0 (SwePub)102072 hsv//swe
650 7a NATURAL SCIENCESx Computer and Information Sciencesx Computer Vision and Robotics0 (SwePub)102072 hsv//eng
650 7a NATURVETENSKAPx Fysikx Atom- och molekylfysik och optik0 (SwePub)103022 hsv//swe
650 7a NATURAL SCIENCESx Physical Sciencesx Atom and Molecular Physics and Optics0 (SwePub)103022 hsv//eng
653 a Circle detection
653 a Randomized algorithm
653 a Sampling strategy
653 a Isosceles triangles
653 a datoriserad bildanalys
653 a Computerized Image Analysis
7001 a Wiklund, Kristeru Umeå universitet,Institutionen för fysik4 aut0 (Swepub:umu)krvi0001
7001 a Andersson, Magnusu Umeå universitet,Institutionen för fysik4 aut0 (Swepub:umu)musann96
7102 a Umeå universitetb Institutionen för fysik4 org
7730 t Pattern Recognitiond : Elsevierg 54, s. 218-228q 54<218-228x 0031-3203x 1873-5142
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-112312
8564 8u https://doi.org/10.1016/j.patcog.2015.12.004

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