RHT: Rolling Hough Transform

Discussion topics for individual codes
Post Reply
Ada Coda
ASCL Robot
Posts: 1708
Joined: Thu May 08, 2014 5:37 am

RHT: Rolling Hough Transform

Post by Ada Coda » Tue Mar 31, 2020 6:34 pm

RHT: Rolling Hough Transform

Abstract: The RHT (Rolling Hough Transform) measures linear intensity as a function of orientation in images. This machine vision algorithm works on any image-space (2D) data, and quantifies the presence of linear structure as a function of orientation. The RHT can be used to identify linear features in images, to quantify the orientation of structure in images, and to map image intensity from 2D x-y space to 3D x-y-orientation space. An option in the code allows the user to quantify intensity as a function of direction (modulo 2pi) rather than orientation (modulo pi). The RHT was first used to discover that filamentary structures in neutral hydrogen emission are aligned with the ambient magnetic field.

Credit: Clark, Susan E.; Peek, Josh; Putman, Mary; Schudel, Lowell; Jaspers, Rutger

Site: https://github.com/seclark/RHT
https://ui.adsabs.harvard.edu/abs/2014ApJ...789...82C

Bibcode: 2020ascl.soft03005C

Preferred citation method: Clark, Peek, & Putman 2014, ApJ 789, 82 https://ui.adsabs.harvard.edu/abs/2014ApJ...789...82C

ID: ascl:2003.005
Last edited by Ada Coda on Sun Apr 26, 2020 6:07 pm, edited 1 time in total.
Reason: Updated code entry.

Post Reply