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  2. Randomized Hough transform - Wikipedia

    en.wikipedia.org/wiki/Randomized_Hough_Transform

    Hough transforms are techniques for object detection, a critical step in many implementations of computer vision, or data mining from images. Specifically, the Randomized Hough transform is a probabilistic variant to the classical Hough transform, and is commonly used to detect curves (straight line, circle, ellipse, etc.) [1] The basic idea of Hough transform (HT) is to implement a voting ...

  3. Hough transform - Wikipedia

    en.wikipedia.org/wiki/Hough_transform

    Yonghong Xie and Qiang Ji give an efficient way of implementing the Hough transform for ellipse detection by overcoming the memory issues. [18] As discussed in the algorithm (on page 2 of the paper), this approach uses only a one-dimensional accumulator (for the minor axis) in order to detect ellipses in the image.

  4. Generalised Hough transform - Wikipedia

    en.wikipedia.org/wiki/Generalised_Hough_transform

    The generalized Hough transform (GHT), introduced by Dana H. Ballard in 1981, is the modification of the Hough transform using the principle of template matching. [1] The Hough transform was initially developed to detect analytically defined shapes (e.g., line, circle, ellipse etc.). In these cases, we have knowledge of the shape and aim to ...

  5. Line detection - Wikipedia

    en.wikipedia.org/wiki/Line_detection

    The Hough transform [3] can be used to detect lines and the output is a parametric description of the lines in an image, for example ρ = r cos(θ) + c sin(θ). [1] If there is a line in a row and column based image space, it can be defined ρ, the distance from the origin to the line along a perpendicular to the line, and θ, the angle of the perpendicular projection from the origin to the ...

  6. Random sample consensus - Wikipedia

    en.wikipedia.org/wiki/Random_sample_consensus

    A simple example is fitting a line in two dimensions to a set of observations. Assuming that this set contains both inliers, i.e., points which approximately can be fitted to a line, and outliers, points which cannot be fitted to this line, a simple least squares method for line fitting will generally produce a line with a bad fit to the data including inliers and outliers.

  7. 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.

  8. Elliptical distribution - Wikipedia

    en.wikipedia.org/wiki/Elliptical_distribution

    Because the variable x enters the density function quadratically, all elliptical distributions are symmetric about . If two subsets of a jointly elliptical random vector are uncorrelated , then if their means exist they are mean independent of each other (the mean of each subvector conditional on the value of the other subvector equals the ...

  9. Corner detection - Wikipedia

    en.wikipedia.org/wiki/Corner_detection

    Corner detection is an approach used within computer vision systems to extract certain kinds of features and infer the contents of an image. Corner detection is frequently used in motion detection, image registration, video tracking, image mosaicing, panorama stitching, 3D reconstruction and object recognition.