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  2. Hough transform - Wikipedia

    en.wikipedia.org/wiki/Hough_transform

    The Hough transform as it is universally used today was invented by Richard Duda and Peter Hart in 1972, who called it a "generalized Hough transform" [3] after the related 1962 patent of Paul Hough. [ 4 ] [ 5 ] The transform was popularized in the computer vision community by Dana H. Ballard through a 1981 journal article titled " Generalizing ...

  3. Random sample consensus - Wikipedia

    en.wikipedia.org/wiki/Random_sample_consensus

    An advantage of RANSAC is its ability to do robust estimation [3] of the model parameters, i.e., it can estimate the parameters with a high degree of accuracy even when a significant number of outliers are present in the data set. A disadvantage of RANSAC is that there is no upper bound on the time it takes to compute these parameters (except ...

  4. Spatial verification - Wikipedia

    en.wikipedia.org/wiki/Spatial_verification

    Spatial verification is a technique in which similar locations can be identified in an automated way through a sequence of images. The general method involves identifying a correlation between certain points among sets images, using techniques similar to those used for image registration.

  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. 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 ...

  7. Point-set registration - Wikipedia

    en.wikipedia.org/wiki/Point-set_registration

    Point set registration is the process of aligning two point sets. Here, the blue fish is being registered to the red fish. In computer vision, pattern recognition, and robotics, point-set registration, also known as point-cloud registration or scan matching, is the process of finding a spatial transformation (e.g., scaling, rotation and translation) that aligns two point clouds.

  8. 2 Stocks to Buy Before 2025 - AOL

    www.aol.com/2-stocks-buy-2025-003155229.html

    Reportedly, CEO Andy Jassy wants to up the ratio of contributors to managers by 15% minimum by the second quarter of next year, an effort that could shore up $3 billion.

  9. 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.