Effective method for ellipse extraction and integration for spacecraft images

Liu, Chang; Hu, Weiduo

doi:10.1117/1.oe.52.5.057002

Cited by 20 publications

(14 citation statements)

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“…This method is inefficient as there exist so many combinations of five points and one has to calculate ellipse parameters for each arXiv:1608.07470v1 [cs.CV] 26 Aug 2016 five-point combination. Instead of directly calculating the ellipse parameters, Liu and Hu [22] use geometric distances of points to a conic in order to evaluate the similarity between any two of selected arcs. There are still a large number of wrong arcs combinations, and the computation of distances between points and arcs lower down its efficiency.…”

Section: Introductionmentioning

confidence: 99%

A Fast Ellipse Detector Using Projective Invariant Pruning

Jia

Fan

Luo

et al. 2017

IEEE Trans. on Image Process.

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Detecting elliptical objects from an image is a central task in robot navigation and industrial diagnosis, where the detection time is always a critical issue. Existing methods are hardly applicable to these real-time scenarios of limited hardware resource due to the huge number of fragment candidates (edges or arcs) for fitting ellipse equations. In this paper, we present a fast algorithm detecting ellipses with high accuracy. The algorithm leverages a newly developed projective invariant to significantly prune the undesired candidates and to pick out elliptical ones. The invariant is able to reflect the intrinsic geometry of a planar curve, giving the value of -1 on any three collinear points and +1 for any six points on an ellipse. Thus, we apply the pruning and picking by simply comparing these binary values. Moreover, the calculation of the invariant only involves the determinant of a 3×3 matrix. Extensive experiments on three challenging data sets with 648 images demonstrate that our detector runs 20%-50% faster than the state-of-the-art algorithms with the comparable or higher precision.

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Section: Introductionmentioning

confidence: 99%

A Fast Ellipse Detector Using Projective Invariant Pruning

Jia

Fan

Luo

et al. 2017

IEEE Trans. on Image Process.

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“…Geometric distance from point to conic is significant to conic fitting; therefore many scholars [3,[22][23][24] have devoted themselves to researching this issue. For example, Kanatani [22] proposed an iterative method which truncates the higher-order terms of the geometric distance of a point.…”

Section: Overviewmentioning

confidence: 99%

Effective ellipse detector with polygonal curve and likelihood ratio test

Liu

et al. 2015

IET Computer Vision

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A robust ellipse detector is proposed. The detector preprocesses the edge map by removing all the isolated points and conjunction points, and exploits polygonal curve to extract the elliptical arcs. A non‐iterative geometric distance computation method is presented to serve a criterion which identifies the elliptical arcs belonging to the same ellipse by likelihood ratio test and fit ellipses to those merged arcs. The authors test their algorithm on both synthetic and real images, and the experimental results show a good performance of their algorithm.

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“…(12) to (14), it can be deduced that at the initial step of iterations when i ¼ 0, λ 0 can be calculated to be 2, and then t 0 ¼ λ 0F0 ¼ 2F 0 . (12) to (14), it can be deduced that at the initial step of iterations when i ¼ 0, λ 0 can be calculated to be 2, and then t 0 ¼ λ 0F0 ¼ 2F 0 .…”

Section: Random Outlier Pointsmentioning

confidence: 99%

“…These projected spots are detected from the captured image and then their centers are extracted. [5][6][7][8][9][10][11][12][13][14][15] HT is based on clustering or voting and is relatively robust against outliers. Therefore, it is very critical to accurately and quickly extract centers of spots for 3-D reconstruction, especially with a lot of noise in the captured image.…”

Section: Introductionmentioning

confidence: 99%

Iteration-based direct ellipse-specific algebraic fitting method of incomplete spots for onsite three-dimensional measurement

Wang

Zhen

et al. 2015

Opt. Eng

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The direct ellipse-specific algebraic fitting (DESAF) method proposed by Fitzgibbon is a classical method to fit an ellipse from discrete points. Generally, for a complete spot, an ellipse, which coincides well with the complete contour of the spot, can be fitted by DESAF. However, for an incomplete spot damaged by some noises such as nonuniform optical surfaces, depth steps, and occlusion, DESAF would fit an incorrect ellipse which could not accurately match the complete contour of the spot. We analyze this problem encountered in the onsite three-dimensional measurement of hull plates and propose a method to remove these outlier points from the contours of incomplete spots. The experiments of computer simulated data and real data demonstrate that the proposed method can dramatically remove the outlier points from the contour and improve the detection accuracy of the center of the incomplete spot.

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Effective method for ellipse extraction and integration for spacecraft images

Cited by 20 publications

References 0 publications

A Fast Ellipse Detector Using Projective Invariant Pruning

A Fast Ellipse Detector Using Projective Invariant Pruning

Effective ellipse detector with polygonal curve and likelihood ratio test

Iteration-based direct ellipse-specific algebraic fitting method of incomplete spots for onsite three-dimensional measurement

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