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  2. Midpoint circle algorithm - Wikipedia

    en.wikipedia.org/wiki/Midpoint_circle_algorithm

    A circle of radius 23 drawn by the Bresenham algorithm. In computer graphics, the midpoint circle algorithm is an algorithm used to determine the points needed for rasterizing a circle. It is a generalization of Bresenham's line algorithm. The algorithm can be further generalized to conic sections. [1] [2] [3]

  3. Bifurcation diagram - Wikipedia

    en.wikipedia.org/wiki/Bifurcation_diagram

    Symmetry breaking in pitchfork bifurcation as the parameter ε is varied. ε = 0 is the case of symmetric pitchfork bifurcation.. In a dynamical system such as ¨ + (;) + =, which is structurally stable when , if a bifurcation diagram is plotted, treating as the bifurcation parameter, but for different values of , the case = is the symmetric pitchfork bifurcation.

  4. Xiaolin Wu's line algorithm - Wikipedia

    en.wikipedia.org/wiki/Xiaolin_Wu's_line_algorithm

    An extension to the algorithm for circle drawing was presented by Xiaolin Wu in the book Graphics Gems II. Just as the line drawing algorithm is a replacement for Bresenham's line drawing algorithm, the circle drawing algorithm is a replacement for Bresenham's circle drawing algorithm.

  5. Hough transform - Wikipedia

    en.wikipedia.org/wiki/Hough_transform

    scikit-image Hough-transform for line, circle and ellipse, implemented in Python. Hough transform based on wavelet filtering, to detect a circle of a particular radius. (Matlab code.) Hough transform for lines using MATLAB Archived 2014-04-13 at the Wayback Machine; Hough transform for circles in MATLAB; KHT – C++ source code.

  6. Curve fitting - Wikipedia

    en.wikipedia.org/wiki/Curve_fitting

    Fitting of a noisy curve by an asymmetrical peak model, with an iterative process (Gauss–Newton algorithm with variable damping factor α).Curve fitting [1] [2] is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, [3] possibly subject to constraints.

  7. Smallest-circle problem - Wikipedia

    en.wikipedia.org/wiki/Smallest-circle_problem

    The algorithm selects one point p randomly and uniformly from P, and recursively finds the minimal circle containing P – {p}, i.e. all of the other points in P except p. If the returned circle also encloses p, it is the minimal circle for the whole of P and is returned. Otherwise, point p must lie on the boundary of the result circle.

  8. Gauss circle problem - Wikipedia

    en.wikipedia.org/wiki/Gauss_circle_problem

    Gauss's circle problem asks how many points there are inside this circle of the form (,) where and are both integers. Since the equation of this circle is given in Cartesian coordinates by x 2 + y 2 = r 2 {\displaystyle x^{2}+y^{2}=r^{2}} , the question is equivalently asking how many pairs of integers m and n there are such that

  9. Circle Hough Transform - Wikipedia

    en.wikipedia.org/wiki/Circle_Hough_Transform

    The circle Hough Transform (CHT) is a basic feature extraction technique used in digital image processing for detecting circles in imperfect images. The circle candidates are produced by “voting” in the Hough parameter space and then selecting local maxima in an accumulator matrix. It is a specialization of the Hough transform.