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  2. Hough transform - Wikipedia

    en.wikipedia.org/wiki/Hough_transform

    The Hough transform is a feature extraction technique used in image analysis, computer vision, pattern recognition, and digital image processing. [1] [2] The purpose of the technique is to find imperfect instances of objects within a certain class of shapes by a voting procedure.

  3. 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 ...

  4. Generalised Hough transform - Wikipedia

    en.wikipedia.org/wiki/Generalised_Hough_transform

    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 find out its location and orientation in the image. This modification enables the Hough transform to be used to detect an arbitrary object described with its model.

  5. 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 ...

  6. 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.

  7. Random sample consensus - Wikipedia

    en.wikipedia.org/wiki/Random_sample_consensus

    All the data points (of the original data) that fit the estimated model well, according to some model-specific loss function, are called the consensus set (i.e., the set of inliers for the model). The estimated model is reasonably good if sufficiently many data points have been classified as a part of the consensus set.

  8. 10 NFL records that could be broken in 2024 season: Will ...

    www.aol.com/10-nfl-records-could-broken...

    With three weeks left in the 2024 NFL regular season, it seems likely that at least a few records will be broken. Keep an eye on these marks.

  9. Edge detection - Wikipedia

    en.wikipedia.org/wiki/Edge_detection

    The phase stretch transform or PST is a physics-inspired computational approach to signal and image processing. One of its utilities is for feature detection and classification. [20] [21] PST is a spin-off from research on the time stretch dispersive Fourier transform. PST transforms the image by emulating propagation through a diffractive ...