The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Randomized Hough Transform
Abstract
Proposed in 1962, the Hough transform (HT) has been widely applied and investigated for detecting curves, shapes, and motions in the fields of image processing and computer vision. However, the HT has several shortcomings, including high computational cost, low detection accuracy, vulnerability to noise, and possibility of missing objects. Many efforts target at solving some of the problems for decades, while the key idea remains more or less the same. Proposed in 1989 and further developed thereafter, the Randomized Hough Transform (RHT) manages to considerably overcome these shortcomings via innovations on the fundamental mechanisms, with random sampling in place of pixel scanning, converging mapping in place of diverging mapping, and dynamic storage in place of accumulation array. This article will provides an overview on advances and applications of RHT in the past one and half decades.
Related Content
Kamel Mouloudj, Vu Lan Oanh LE, Achouak Bouarar, Ahmed Chemseddine Bouarar, Dachel Martínez Asanza, Mayuri Srivastava.
© 2024.
20 pages.
|
José Eduardo Aleixo, José Luís Reis, Sandrina Francisca Teixeira, Ana Pinto de Lima.
© 2024.
52 pages.
|
Jorge Figueiredo, Isabel Oliveira, Sérgio Silva, Margarida Pocinho, António Cardoso, Manuel Pereira.
© 2024.
24 pages.
|
Fatih Pinarbasi.
© 2024.
20 pages.
|
Stavros Kaperonis.
© 2024.
25 pages.
|
Thomas Rui Mendes, Ana Cristina Antunes.
© 2024.
24 pages.
|
Nuno Geada.
© 2024.
12 pages.
|
|
|