Subpixel registration using a concentric ring fiducial

O’Gorman, Lawrence; Bruckstein, Alfred M.; Bose, C.B.; Amir, I.

doi:10.1109/icpr.1990.119365

Cited by 16 publications

(9 citation statements)

References 10 publications

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“…It would be interesting to determine how robust our methods are with respect to noise. Empirical results of O'Gorman et al 7 indicate that circular fiducials are indeed robust.…”

Section: Discussionmentioning

confidence: 87%

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Subpixel Image Registration Using Circular Fiducials

Efrat¹,

Gotsman²

1994

Int. J. Comput. Geom. Appl.

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The design of fiducials for precise image registration is of major practical importance in computer vision, especially in automatic inspection applications. We analyze the subpixel registration accuracy that can, and cannot, be achieved by some rotation-invariant fiducials, and present and analyze efficient algorithms for the registration procedure. We rely on some old and new results from lattice geometry and number theory and efficient computational-geometric methods.

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“…It would be interesting to determine how robust our methods are with respect to noise. Empirical results of O'Gorman et al 7 indicate that circular fiducials are indeed robust.…”

Section: Discussionmentioning

confidence: 87%

“…Because of this, O'Gorman et al 7 suggest that more precision may be obtained by adding more "circumferences" to the fiducial. This is achieved by using not a solid disk, but a "bulleye" pattern consisting of concentric rings of alternating colors.…”

Section: Introductionmentioning

confidence: 99%

Subpixel Image Registration Using Circular Fiducials

Efrat¹,

Gotsman²

1994

Int. J. Comput. Geom. Appl.

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“…It should be noted from Figure 7 that the image of the center of circles DOES NOT the center of the conics and cannot be detected using the general moment based methods [7,10]. Heikkilä and Silven [10] used a recursive procedure with the camera parameters to correct the bias between the imaged center of circles and center of conics after knowing the latter positions.…”

Section: Resultsmentioning

confidence: 99%

Detection of concentric circles for camera calibration

Jiang

Quan

2005

Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1

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The geometry of plane-based calibration methods is well understood, but some user interaction is often needed in practice for feature detection. This paper presents a fully automatic calibration system that uses patterns of pairs of concentric circles. The key observation is to introduce a geometric method that constructs a sequence of points strictly convergent to the image of the circle center from an arbitrary point. The method automatically detects the points of the pattern features by the construction method, and identify them by invariants. It then takes advantage of homological constraints to consistently and optimally estimate the features in the image. The experiments demonstrate the robustness and the accuracy of the new method.

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“…These authors also achieved good results when evaluating a 3 point least squares fit to a circle. Earlier worked was also published using the centroid approach to finding the center of an object [4]. The analysis included image noise on the precision of the centroid technique on different target geometries.…”

Section: Introductionmentioning

confidence: 99%

Sub pixel accuracy of fiducial marks using least square estimator

Coumou¹

2005

SPIE Proceedings

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An image processing architecture has been developed that executes a concatenated algorithm to determine the presence of multiple fiducial marks on an image plane, locates the estimated position of the fiducial marks in the image, calculates subpixel accuracy of the fiducial mark, and translates the x and y coordinates of the fiducial marks to absolute distance and phase relationships between fiducial marks. The fiducial mark is an object with an outer circular boundary and two inner lines that intersect to provide an object with symmetry. This symmetry is crucial for the requirements of rotation and scaling invariant, specifically for the process of identifying the presence of the fiducial mark in the image plane. Video is used for imagery of the fiducial marks.

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Subpixel registration using a concentric ring fiducial

Cited by 16 publications

References 10 publications

Subpixel Image Registration Using Circular Fiducials

Subpixel Image Registration Using Circular Fiducials

Detection of concentric circles for camera calibration

Sub pixel accuracy of fiducial marks using least square estimator

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