ElliFit: An unconstrained, non-iterative, least squares based geometric Ellipse Fitting method

Prasad, Dilip K.; Leung, M.K.H.; Quek, Chai

doi:10.1016/j.patcog.2012.11.007

Cited by 145 publications

(57 citation statements)

References 27 publications

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“…Some of the best known image processing approaches for detection and adjustment of ellipses are the Hough Transform456, Random Sample Consensus (RANSAC)78910 and least squares11121314. Grouping approaches (Hough Transform and RANSAC) are robust against noise and detect multiple ellipses, but are relatively slow, require a lot of memory and suffer from low accuracy.…”

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confidence: 99%

Automatic detection and measurement of viral replication compartments by ellipse adjustment

Suárez

Guerrero

Hidalgo

et al. 2016

Sci Rep

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Viruses employ a variety of strategies to hijack cellular activities through the orchestrated recruitment of macromolecules to specific virus-induced cellular micro-environments. Adenoviruses (Ad) and other DNA viruses induce extensive reorganization of the cell nucleus and formation of nuclear Replication Compartments (RCs), where the viral genome is replicated and expressed. In this work an automatic algorithm designed for detection and segmentation of RCs using ellipses is presented. Unlike algorithms available in the literature, this approach is deterministic, automatic, and can adjust multiple RCs using ellipses. The proposed algorithm is non iterative, computationally efficient and is invariant to affine transformations. The method was validated over both synthetic images and more than 400 real images of Ad-infected cells at various timepoints of the viral replication cycle obtaining relevant information about the biogenesis of adenoviral RCs. As proof of concept the algorithm was then used to quantitatively compare RCs in cells infected with the adenovirus wild type or an adenovirus mutant that is null for expression of a viral protein that is known to affect activities associated with RCs that result in deficient viral progeny production.

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confidence: 99%

Automatic detection and measurement of viral replication compartments by ellipse adjustment

Suárez

Guerrero

Hidalgo

et al. 2016

Sci Rep

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“…2(c). We cluster them in a hierarchical agglomerative manner and fit ellipses to each resulting cluster using a noniterative least squares approach of [51]. In all our experiments, we set the size of the suppression neighborhood to seven pixels because this is the minimum number of points required to reliably fit an ellipse using this approach.…”

Section: Building Hierarchy Graphsmentioning

confidence: 99%

Network Flow Integer Programming to Track Elliptical Cells in Time-Lapse Sequences

Türetken

Wang

Becker

et al. 2017

IEEE Trans. Med. Imaging

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Abstract-We propose a novel approach to automatically tracking elliptical cell populations in time-lapse image sequences. Given an initial segmentation, we account for partial occlusions and overlaps by generating an over-complete set of competing detection hypotheses. To this end, we fit ellipses to portions of the initial regions and build a hierarchy of ellipses, which are then treated as cell candidates. We then select temporally consistent ones by solving to optimality an integer program with only one type of flow variables. This eliminates the need for heuristics to handle missed detections due to partial occlusions and complex morphology. We demonstrate the effectiveness of our approach on a range of challenging sequences consisting of clumped cells and show that it outperforms state-of-the-art techniques.

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“…Then, we extracted the coordinates of all of the 2 × 49 feature points of the tested image, using the ellipse fitting method. 23 The results of this extraction, after correcting for the image distortion, are shown in Fig. 11(b).…”

Section: Validation Experimentsmentioning

confidence: 99%

Epipolar constraint of single-camera mirror binocular stereo vision systems

2017

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Abstract. Virtual binocular sensors, composed of a camera and catoptric mirrors, have become popular among machine vision researchers, owing to their high flexibility and compactness. Usually, the tested target is projected onto a camera at different reflection times, and feature matching is performed using one image. To establish the geometric principles of the feature-matching process of a mirror binocular stereo vision system, we proposed a single-camera model with the epipolar constraint for matching the mirrored features. The constraint between the image coordinates of the real target and its mirror reflection is determined, which can be used to eliminate nonmatching points in the feature-matching process of a mirror binocular system. To validate the epipolar constraint model and to evaluate its performance in practical applications, we performed realistic matching experiments and analysis using a mirror binocular stereo vision system. Our results demonstrate the feasibility of the proposed model, suggesting a method for considerable improvement of efficacy of the process for matching mirrored features.

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ElliFit: An unconstrained, non-iterative, least squares based geometric Ellipse Fitting method

Cited by 145 publications

References 27 publications

Automatic detection and measurement of viral replication compartments by ellipse adjustment

Automatic detection and measurement of viral replication compartments by ellipse adjustment

Network Flow Integer Programming to Track Elliptical Cells in Time-Lapse Sequences

Epipolar constraint of single-camera mirror binocular stereo vision systems

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