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Journal ArticleDOI

Finding ellipses using the generalised Hough transform

E.R. Davies
- 01 Feb 1989 - 
- Vol. 9, Iss: 2, pp 87-96
TLDR
Here it is shown that a single plane in parameter space can be employed, with a consequent gain in efficiency, and is especially suitable for ellipses of low eccentricity.
About
This article is published in Pattern Recognition Letters.The article was published on 1989-02-01. It has received 80 citations till now. The article focuses on the topics: Generalised Hough transform & Hough transform.

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Citations
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Journal ArticleDOI

A survey of fuzzy clustering

TL;DR: A survey of fuzzy set theory applied in cluster analysis in three categories: the fuzzy clustering based on fuzzy relation, the fuzzy generalized k-nearest neighbor rule, and an overview of a nonparametric classifier.
Proceedings ArticleDOI

A new efficient ellipse detection method

TL;DR: A new method is introduced that takes the advantages of major axis of an ellipse to findEllipse parameter fast and efficiently and only needs a one-dimensional accumulator array to accumulate the length information for minor axis of the ellipSE.
Journal ArticleDOI

Modification of hough transform for circles and ellipses detection using a 2-dimensional array

TL;DR: Techniques aimed at improving the efficiency and reducing the memory size of the accumulator array are presented, which show that only a 2-dimensional array is needed for the detection of circles and ellipses.
Journal ArticleDOI

Adaptive fuzzy c-shells clustering and detection of ellipses

TL;DR: Several generalizations of the fuzzy c-shells (FCS) algorithm are presented for characterizing and detecting clusters that are hyperellipsoidal shells and show that the AFCS algorithm requires less memory than the HT-based methods, and it is at least an order of magnitude faster than theHT approach.
Journal ArticleDOI

Statistical bias of conic fitting and renormalization

TL;DR: A new fitting scheme called renormalization is presented for computing an unbiased estimate by automatically adjusting to noise in a statistical model of noise in terms of the covariance matrix of the N-vector.
References
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Journal ArticleDOI

Use of the Hough transformation to detect lines and curves in pictures

TL;DR: It is pointed out that the use of angle-radius rather than slope-intercept parameters simplifies the computation further, and how the method can be used for more general curve fitting.
Journal ArticleDOI

Generalizing the hough transform to detect arbitrary shapes

TL;DR: It is shown how the boundaries of an arbitrary non-analytic shape can be used to construct a mapping between image space and Hough transform space, which makes the generalized Houghtransform a kind of universal transform which can beused to find arbitrarily complex shapes.
Journal ArticleDOI

Finding circles by an array of accumulators

TL;DR: This procedure is an extension and improvement of the circle-finding concept sketched by Duda and Hart as an extension of the Hough straight-line finder.
Book ChapterDOI

Recognising and Locating Partially Visible Objects: The Local-Feature-Focus Method

TL;DR: In this paper, a new method of locating partially visible two-dimensional objects is presented, which is applicable to complex industrial parts that may contain several occurrences of local features, such as holes and corners.
Journal ArticleDOI

Detection of Ellipses by a Modified Hough Transformation

Tsuji, +1 more
TL;DR: This correspondence proposes a modified method which utilizes two properties of an ellipse in such a way that it iteratively searches for clusters in two different parameter spaces to find almost complete ellipses, then evaluates their parameters by the least mean squares method.
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