Hough transform

<p>The Hough transform  is a <a href="/facts/Feature_extraction/BSMX5e8I">feature extraction</a> technique used in <a href="/facts/Image_analysis/woLB8cX7">image analysis</a>, <a href="/facts/Computer_vision/Tl2Yyk66">computer vision</a>, <a href="/facts/Pattern_recognition/o1s38opj">pattern recognition</a>, and <a href="/facts/Digital_image_processing/zenalNCf">digital image processing</a>. The purpose of the technique is to find imperfect instances of objects within a certain class of shapes by a voting procedure. This voting procedure is carried out in a <a href="/facts/Parameter_space/LpdMY5gc">parameter space</a>, from which object candidates are obtained as local maxima in a so-called accumulator space that is explicitly constructed by the algorithm for computing the Hough transform.  Mathematically it is simply the  <a href="/facts/Radon_transform/JskFJRMS">Radon transform</a> in the plane, known since at least 1917, but the Hough transform refers to its use in image analysis. 
</p><p>The classical Hough transform was concerned with the identification of <a href="/facts/Line_(mathematics)/gJqsr4Gj">lines</a> in the image, but later the Hough transform has been extended to identifying positions of arbitrary shapes, most commonly <a href="/facts/Circle/9fy5ggKn">circles</a> or <a href="/facts/Ellipse/1wUDnGxY">ellipses</a>. The Hough transform as it is universally used today was invented by <a href="/facts/Richard_Duda/d7nAjctd">Richard Duda</a> and <a href="/facts/Peter_E._Hart/pKSPzx0Q">Peter Hart</a> in 1972, who called it a "generalized Hough transform" after the related 1962 patent of Paul Hough. The transform was popularized in the <a href="/facts/Computer_vision/Tl2Yyk66">computer vision</a> community by <a href="/facts/Dana_H._Ballard/uqF8Brmq">Dana H. Ballard</a> through a 1981 journal article titled "<a href="/facts/Generalised_Hough_transform/ARs3VIlD">Generalizing the Hough transform to detect arbitrary shapes</a>".
</p>

Hough transform open-in-new

Hough transform