Enum opencv::imgproc::HoughModes
source · #[repr(C)]pub enum HoughModes {
HOUGH_STANDARD = 0,
HOUGH_PROBABILISTIC = 1,
HOUGH_MULTI_SCALE = 2,
HOUGH_GRADIENT = 3,
HOUGH_GRADIENT_ALT = 4,
}
Expand description
Variants of a Hough transform
Variants§
HOUGH_STANDARD = 0
classical or standard Hough transform. Every line is represented by two floating-point
numbers , where
is a distance between (0,0) point and the line,
and
is the angle between x-axis and the normal to the line. Thus, the matrix must
be (the created sequence will be) of CV_32FC2 type
HOUGH_PROBABILISTIC = 1
probabilistic Hough transform (more efficient in case if the picture contains a few long linear segments). It returns line segments rather than the whole line. Each segment is represented by starting and ending points, and the matrix must be (the created sequence will be) of the CV_32SC4 type.
HOUGH_MULTI_SCALE = 2
multi-scale variant of the classical Hough transform. The lines are encoded the same way as HOUGH_STANDARD.
HOUGH_GRADIENT = 3
basically 21HT, described in Yuen90
HOUGH_GRADIENT_ALT = 4
variation of HOUGH_GRADIENT to get better accuracy
Trait Implementations§
source§impl Clone for HoughModes
impl Clone for HoughModes
source§fn clone(&self) -> HoughModes
fn clone(&self) -> HoughModes
1.0.0 · source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read moresource§impl Debug for HoughModes
impl Debug for HoughModes
source§impl PartialEq for HoughModes
impl PartialEq for HoughModes
source§fn eq(&self, other: &HoughModes) -> bool
fn eq(&self, other: &HoughModes) -> bool
self
and other
values to be equal, and is used
by ==
.