Trait opencv::features2d::MSER

pub trait MSER: Feature2DTrait {
    fn as_raw_MSER(&self) -> *mut c_void;

    fn detect_regions(
        &mut self, 
        image: &dyn ToInputArray, 
        msers: &mut VectorOfVectorOfPoint, 
        bboxes: &mut VectorOfRect
    ) -> Result<()> { ... }
    fn set_delta(&mut self, delta: i32) -> Result<()> { ... }
    fn get_delta(&self) -> Result<i32> { ... }
    fn set_min_area(&mut self, min_area: i32) -> Result<()> { ... }
    fn get_min_area(&self) -> Result<i32> { ... }
    fn set_max_area(&mut self, max_area: i32) -> Result<()> { ... }
    fn get_max_area(&self) -> Result<i32> { ... }
    fn set_pass2_only(&mut self, f: bool) -> Result<()> { ... }
    fn get_pass2_only(&self) -> Result<bool> { ... }
    fn get_default_name(&self) -> Result<String> { ... }
}

Maximally stable extremal region extractor

The class encapsulates all the parameters of the %MSER extraction algorithm (see wiki article).

• there are two different implementation of %MSER: one for grey image, one for color image

• the grey image algorithm is taken from: nister2008linear ; the paper claims to be faster than union-find method; it actually get 1.5~2m/s on my centrino L7200 1.2GHz laptop.

• the color image algorithm is taken from: forssen2007maximally ; it should be much slower than grey image method ( 3~4 times ); the chi_table.h file is taken directly from paper's source code which is distributed under GPL.

• (Python) A complete example showing the use of the %MSER detector can be found at samples/python/mser.py

Required methods

fn as_raw_MSER(&self) -> *mut c_void

Loading content...

Provided methods

fn detect_regions(
    &mut self,
    image: &dyn ToInputArray,
    msers: &mut VectorOfVectorOfPoint,
    bboxes: &mut VectorOfRect
) -> Result<()>

Detect %MSER regions

Parameters

• image: input image (8UC1, 8UC3 or 8UC4, must be greater or equal than 3x3)
• msers: resulting list of point sets
• bboxes: resulting bounding boxes

fn set_delta(&mut self, delta: i32) -> Result<()>

fn get_delta(&self) -> Result<i32>

fn set_min_area(&mut self, min_area: i32) -> Result<()>

fn get_min_area(&self) -> Result<i32>

fn set_max_area(&mut self, max_area: i32) -> Result<()>

fn get_max_area(&self) -> Result<i32>

fn set_pass2_only(&mut self, f: bool) -> Result<()>

fn get_pass2_only(&self) -> Result<bool>

fn get_default_name(&self) -> Result<String>

Loading content...

Methods

impl<'_> dyn MSER + '_

pub fn create(
    _delta: i32,
    _min_area: i32,
    _max_area: i32,
    _max_variation: f64,
    _min_diversity: f64,
    _max_evolution: i32,
    _area_threshold: f64,
    _min_margin: f64,
    _edge_blur_size: i32
) -> Result<PtrOfMSER>

Full consturctor for %MSER detector

Parameters

• _delta: it compares
• _min_area: prune the area which smaller than minArea
• _max_area: prune the area which bigger than maxArea
• _max_variation: prune the area have similar size to its children
• _min_diversity: for color image, trace back to cut off mser with diversity less than min_diversity
• _max_evolution: for color image, the evolution steps
• _area_threshold: for color image, the area threshold to cause re-initialize
• _min_margin: for color image, ignore too small margin
• _edge_blur_size: for color image, the aperture size for edge blur

C++ default parameters

• _delta: 5
• _min_area: 60
• _max_area: 14400
• _max_variation: 0.25
• _min_diversity: .2
• _max_evolution: 200
• _area_threshold: 1.01
• _min_margin: 0.003
• _edge_blur_size: 5

Implementors

impl MSER for PtrOfMSER

fn as_raw_MSER(&self) -> *mut c_void

Loading content...