[][src]Trait opencv::text::ERStatTrait

pub trait ERStatTrait {
    fn as_raw_ERStat(&self) -> *mut c_void;

    fn pixel(&self) -> i32 { ... }
fn set_pixel(&mut self, val: i32) { ... }
fn level(&self) -> i32 { ... }
fn set_level(&mut self, val: i32) { ... }
fn area(&self) -> i32 { ... }
fn set_area(&mut self, val: i32) { ... }
fn perimeter(&self) -> i32 { ... }
fn set_perimeter(&mut self, val: i32) { ... }
fn euler(&self) -> i32 { ... }
fn set_euler(&mut self, val: i32) { ... }
fn rect(&self) -> Rect { ... }
fn set_rect(&mut self, val: Rect) { ... }
fn raw_moments(&mut self) -> &mut [f64; 2] { ... }
fn central_moments(&mut self) -> &mut [f64; 3] { ... }
fn med_crossings(&self) -> f32 { ... }
fn set_med_crossings(&mut self, val: f32) { ... }
fn hole_area_ratio(&self) -> f32 { ... }
fn set_hole_area_ratio(&mut self, val: f32) { ... }
fn convex_hull_ratio(&self) -> f32 { ... }
fn set_convex_hull_ratio(&mut self, val: f32) { ... }
fn num_inflexion_points(&self) -> f32 { ... }
fn set_num_inflexion_points(&mut self, val: f32) { ... }
fn pixels(&mut self) -> VectorOfi32 { ... }
fn set_pixels(&mut self, val: &mut VectorOfi32) { ... }
fn probability(&self) -> f64 { ... }
fn set_probability(&mut self, val: f64) { ... }
fn parent(&mut self) -> ERStat { ... }
fn set_parent(&mut self, val: &mut ERStat) { ... }
fn child(&mut self) -> ERStat { ... }
fn set_child(&mut self, val: &mut ERStat) { ... }
fn next(&mut self) -> ERStat { ... }
fn set_next(&mut self, val: &mut ERStat) { ... }
fn prev(&mut self) -> ERStat { ... }
fn set_prev(&mut self, val: &mut ERStat) { ... }
fn local_maxima(&self) -> bool { ... }
fn set_local_maxima(&mut self, val: bool) { ... }
fn max_probability_ancestor(&mut self) -> ERStat { ... }
fn set_max_probability_ancestor(&mut self, val: &mut ERStat) { ... }
fn min_probability_ancestor(&mut self) -> ERStat { ... }
fn set_min_probability_ancestor(&mut self, val: &mut ERStat) { ... } }

The ERStat structure represents a class-specific Extremal Region (ER).

An ER is a 4-connected set of pixels with all its grey-level values smaller than the values in its outer boundary. A class-specific ER is selected (using a classifier) from all the ER's in the component tree of the image. :

Required methods

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Provided methods

fn pixel(&self) -> i32

seed point and the threshold (max grey-level value)

fn set_pixel(&mut self, val: i32)

seed point and the threshold (max grey-level value)

fn level(&self) -> i32

fn set_level(&mut self, val: i32)

fn area(&self) -> i32

incrementally computable features

fn set_area(&mut self, val: i32)

incrementally computable features

fn perimeter(&self) -> i32

fn set_perimeter(&mut self, val: i32)

fn euler(&self) -> i32

Euler's number

fn set_euler(&mut self, val: i32)

Euler's number

fn rect(&self) -> Rect

fn set_rect(&mut self, val: Rect)

fn raw_moments(&mut self) -> &mut [f64; 2]

order 1 raw moments to derive the centroid

fn central_moments(&mut self) -> &mut [f64; 3]

order 2 central moments to construct the covariance matrix

fn med_crossings(&self) -> f32

median of the crossings at three different height levels

fn set_med_crossings(&mut self, val: f32)

median of the crossings at three different height levels

fn hole_area_ratio(&self) -> f32

2nd stage features

fn set_hole_area_ratio(&mut self, val: f32)

2nd stage features

fn convex_hull_ratio(&self) -> f32

fn set_convex_hull_ratio(&mut self, val: f32)

fn num_inflexion_points(&self) -> f32

fn set_num_inflexion_points(&mut self, val: f32)

fn pixels(&mut self) -> VectorOfi32

fn set_pixels(&mut self, val: &mut VectorOfi32)

fn probability(&self) -> f64

probability that the ER belongs to the class we are looking for

fn set_probability(&mut self, val: f64)

probability that the ER belongs to the class we are looking for

fn parent(&mut self) -> ERStat

pointers preserving the tree structure of the component tree

fn set_parent(&mut self, val: &mut ERStat)

pointers preserving the tree structure of the component tree

fn child(&mut self) -> ERStat

fn set_child(&mut self, val: &mut ERStat)

fn next(&mut self) -> ERStat

fn set_next(&mut self, val: &mut ERStat)

fn prev(&mut self) -> ERStat

fn set_prev(&mut self, val: &mut ERStat)

fn local_maxima(&self) -> bool

whenever the regions is a local maxima of the probability

fn set_local_maxima(&mut self, val: bool)

whenever the regions is a local maxima of the probability

fn max_probability_ancestor(&mut self) -> ERStat

fn set_max_probability_ancestor(&mut self, val: &mut ERStat)

fn min_probability_ancestor(&mut self) -> ERStat

fn set_min_probability_ancestor(&mut self, val: &mut ERStat)

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Implementors

impl ERStatTrait for ERStat[src]

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