[{"@context":"http:\/\/schema.org\/","@type":"BlogPosting","@id":"https:\/\/wiki.edu.vn\/en\/wiki24\/features-from-accelerated-segment-test\/#BlogPosting","mainEntityOfPage":"https:\/\/wiki.edu.vn\/en\/wiki24\/features-from-accelerated-segment-test\/","headline":"Features from accelerated segment test","name":"Features from accelerated segment test","description":"Features from accelerated segment test (FAST) is a corner detection method, which could be used to extract feature points and","datePublished":"2021-10-19","dateModified":"2021-10-19","author":{"@type":"Person","@id":"https:\/\/wiki.edu.vn\/en\/wiki24\/author\/lordneo\/#Person","name":"lordneo","url":"https:\/\/wiki.edu.vn\/en\/wiki24\/author\/lordneo\/","image":{"@type":"ImageObject","@id":"https:\/\/secure.gravatar.com\/avatar\/c9645c498c9701c88b89b8537773dd7c?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/c9645c498c9701c88b89b8537773dd7c?s=96&d=mm&r=g","height":96,"width":96}},"publisher":{"@type":"Organization","name":"Enzyklop\u00e4die","logo":{"@type":"ImageObject","@id":"https:\/\/wiki.edu.vn\/wiki4\/wp-content\/uploads\/2023\/08\/download.jpg","url":"https:\/\/wiki.edu.vn\/wiki4\/wp-content\/uploads\/2023\/08\/download.jpg","width":600,"height":60}},"image":{"@type":"ImageObject","@id":"https:\/\/upload.wikimedia.org\/wikipedia\/commons\/thumb\/4\/47\/FAST_Corner_Detector.jpg\/220px-FAST_Corner_Detector.jpg","url":"https:\/\/upload.wikimedia.org\/wikipedia\/commons\/thumb\/4\/47\/FAST_Corner_Detector.jpg\/220px-FAST_Corner_Detector.jpg","height":"154","width":"220"},"url":"https:\/\/wiki.edu.vn\/en\/wiki24\/features-from-accelerated-segment-test\/","about":["Wiki"],"wordCount":2790,"articleBody":"Features from accelerated segment test (FAST) is a corner detection method, which could be used to extract feature points and later used to track and map objects in many computer vision tasks. The FAST corner detector was originally developed by Edward Rosten and Tom Drummond, and was published in 2006.[1] The most promising advantage of the FAST corner detector is its computational efficiency. Referring to its name, it is indeed faster than many other well-known feature extraction methods, such as difference of Gaussians (DoG) used by the SIFT, SUSAN and Harris detectors. Moreover, when machine learning techniques are applied, superior performance in terms of computation time and resources can be realised. The FAST corner detector is very suitable for real-time video processing application because of this high-speed performance.Table of ContentsSegment test detector[edit]High-speed test[edit]Improvement with machine learning[edit]Non-maximum suppression[edit]FAST-ER: Enhanced repeatability[edit]Comparison with other detectors[edit]References[edit]Bibliography[edit]External links[edit]Segment test detector[edit]  The pixels used by the FAST corner detectorFAST corner detector uses a circle of 16 pixels (a Bresenham circle of radius 3) to classify whether a candidate point p is actually a corner. Each pixel in the circle is labeled from integer number 1 to 16 clockwise. If a set of N contiguous pixels in the circle are all brighter than the intensity of candidate pixel p (denoted by Ip) plus a threshold value t or all darker than the intensity of candidate pixel p minus threshold value t, then p is classified as corner.  The conditions can be written as:Condition 1: A set of N contiguous pixels S, \u2200x\u2208S{displaystyle forall xin S}, the intensity of x >  Ip + threshold, or I_{p}+t}”\/>Condition 2: A set of N contiguous pixels S, \u2200x\u2208S{displaystyle forall xin S}, Ix"},{"@context":"http:\/\/schema.org\/","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"item":{"@id":"https:\/\/wiki.edu.vn\/en\/wiki24\/#breadcrumbitem","name":"Enzyklop\u00e4die"}},{"@type":"ListItem","position":2,"item":{"@id":"https:\/\/wiki.edu.vn\/en\/wiki24\/features-from-accelerated-segment-test\/#breadcrumbitem","name":"Features from accelerated segment test"}}]}]