Package org.opencv.features2d

Class MSER

java.lang.Object
org.opencv.core.Algorithm
org.opencv.features2d.Feature2D
org.opencv.features2d.MSER
public class MSER extends Feature2D
Maximally stable extremal region extractor The class encapsulates all the parameters of the %MSER extraction algorithm (see [wiki article](http://en.wikipedia.org/wiki/Maximally_stable_extremal_regions)).
  • there are two different implementation of %MSER: one for grey image, one for color image
  • the grey image algorithm is taken from: CITE: 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: CITE: forssen2007maximally ; it should be much slower than grey image method ( 3~4 times )
  • (Python) A complete example showing the use of the %MSER detector can be found at samples/python/mser.py

  • Method Details

    • __fromPtr__

      public static MSER __fromPtr__(long addr)

    • create

      public static MSER create(int delta, int min_area, int max_area, double max_variation, double min_diversity, int max_evolution, double area_threshold, double min_margin, int edge_blur_size)
      Full constructor for %MSER detector
      Parameters:
      delta - it compares \((size_{i}-size_{i-delta})/size_{i-delta}\)
      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
      Returns:
      automatically generated

    • create

      public static MSER create(int delta, int min_area, int max_area, double max_variation, double min_diversity, int max_evolution, double area_threshold, double min_margin)
      Full constructor for %MSER detector
      Parameters:
      delta - it compares \((size_{i}-size_{i-delta})/size_{i-delta}\)
      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
      Returns:
      automatically generated

    • create

      public static MSER create(int delta, int min_area, int max_area, double max_variation, double min_diversity, int max_evolution, double area_threshold)
      Full constructor for %MSER detector
      Parameters:
      delta - it compares \((size_{i}-size_{i-delta})/size_{i-delta}\)
      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
      Returns:
      automatically generated

    • create

      public static MSER create(int delta, int min_area, int max_area, double max_variation, double min_diversity, int max_evolution)
      Full constructor for %MSER detector
      Parameters:
      delta - it compares \((size_{i}-size_{i-delta})/size_{i-delta}\)
      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
      Returns:
      automatically generated

    • create

      public static MSER create(int delta, int min_area, int max_area, double max_variation, double min_diversity)
      Full constructor for %MSER detector
      Parameters:
      delta - it compares \((size_{i}-size_{i-delta})/size_{i-delta}\)
      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
      Returns:
      automatically generated

    • create

      public static MSER create(int delta, int min_area, int max_area, double max_variation)
      Full constructor for %MSER detector
      Parameters:
      delta - it compares \((size_{i}-size_{i-delta})/size_{i-delta}\)
      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
      Returns:
      automatically generated

    • create

      public static MSER create(int delta, int min_area, int max_area)
      Full constructor for %MSER detector
      Parameters:
      delta - it compares \((size_{i}-size_{i-delta})/size_{i-delta}\)
      min_area - prune the area which smaller than minArea
      max_area - prune the area which bigger than maxArea
      Returns:
      automatically generated

    • create

      public static MSER create(int delta, int min_area)
      Full constructor for %MSER detector
      Parameters:
      delta - it compares \((size_{i}-size_{i-delta})/size_{i-delta}\)
      min_area - prune the area which smaller than minArea
      Returns:
      automatically generated

    • create

      public static MSER create(int delta)
      Full constructor for %MSER detector
      Parameters:
      delta - it compares \((size_{i}-size_{i-delta})/size_{i-delta}\)
      Returns:
      automatically generated

    • create

      public static MSER create()
      Full constructor for %MSER detector
      Returns:
      automatically generated

    • detectRegions

      public void detectRegions(Mat image, List<MatOfPoint> msers, MatOfRect bboxes)
      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

    • setDelta

      public void setDelta(int delta)

    • getDelta

      public int getDelta()

    • setMinArea

      public void setMinArea(int minArea)

    • getMinArea

      public int getMinArea()

    • setMaxArea

      public void setMaxArea(int maxArea)

    • getMaxArea

      public int getMaxArea()

    • setMaxVariation

      public void setMaxVariation(double maxVariation)

    • getMaxVariation

      public double getMaxVariation()

    • setMinDiversity

      public void setMinDiversity(double minDiversity)

    • getMinDiversity

      public double getMinDiversity()

    • setMaxEvolution

      public void setMaxEvolution(int maxEvolution)

    • getMaxEvolution

      public int getMaxEvolution()

    • setAreaThreshold

      public void setAreaThreshold(double areaThreshold)

    • getAreaThreshold

      public double getAreaThreshold()

    • setMinMargin

      public void setMinMargin(double min_margin)

    • getMinMargin

      public double getMinMargin()

    • setEdgeBlurSize

      public void setEdgeBlurSize(int edge_blur_size)

    • getEdgeBlurSize

      public int getEdgeBlurSize()

    • setPass2Only

      public void setPass2Only(boolean f)

    • getPass2Only

      public boolean getPass2Only()

    • getDefaultName

      public String getDefaultName()
      Description copied from class: Algorithm
      Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.
      Overrides:
      getDefaultName in class Feature2D
      Returns:
      automatically generated