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virtual void | detectRegions (InputArray image, std::vector< std::vector< Point > > &msers, std::vector< Rect > &bboxes)=0 |
| Detect MSER regions. More...
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virtual double | getAreaThreshold () const =0 |
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virtual String | getDefaultName () const CV_OVERRIDE |
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virtual int | getDelta () const =0 |
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virtual int | getEdgeBlurSize () const =0 |
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virtual int | getMaxArea () const =0 |
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virtual int | getMaxEvolution () const =0 |
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virtual double | getMaxVariation () const =0 |
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virtual int | getMinArea () const =0 |
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virtual double | getMinDiversity () const =0 |
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virtual double | getMinMargin () const =0 |
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virtual bool | getPass2Only () const =0 |
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virtual void | setAreaThreshold (double areaThreshold)=0 |
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virtual void | setDelta (int delta)=0 |
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virtual void | setEdgeBlurSize (int edge_blur_size)=0 |
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virtual void | setMaxArea (int maxArea)=0 |
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virtual void | setMaxEvolution (int maxEvolution)=0 |
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virtual void | setMaxVariation (double maxVariation)=0 |
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virtual void | setMinArea (int minArea)=0 |
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virtual void | setMinDiversity (double minDiversity)=0 |
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virtual void | setMinMargin (double min_margin)=0 |
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virtual void | setPass2Only (bool f)=0 |
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virtual | ~Feature2D () |
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virtual void | compute (InputArray image, std::vector< KeyPoint > &keypoints, OutputArray descriptors) |
| Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (second variant). More...
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virtual void | compute (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, OutputArrayOfArrays descriptors) |
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virtual int | defaultNorm () const |
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virtual int | descriptorSize () const |
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virtual int | descriptorType () const |
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virtual void | detect (InputArray image, std::vector< KeyPoint > &keypoints, InputArray mask=noArray()) |
| Detects keypoints in an image (first variant) or image set (second variant). More...
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virtual void | detect (InputArrayOfArrays images, std::vector< std::vector< KeyPoint > > &keypoints, InputArrayOfArrays masks=noArray()) |
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virtual void | detectAndCompute (InputArray image, InputArray mask, std::vector< KeyPoint > &keypoints, OutputArray descriptors, bool useProvidedKeypoints=false) |
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virtual bool | empty () const CV_OVERRIDE |
| Return true if detector object is empty. More...
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void | read (const String &fileName) |
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virtual void | read (const FileNode &) CV_OVERRIDE |
| Reads algorithm parameters from a file storage. More...
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void | write (const String &fileName) const |
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virtual void | write (FileStorage &) const CV_OVERRIDE |
| Stores algorithm parameters in a file storage. More...
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void | write (FileStorage &fs, const String &name) const |
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void | write (const Ptr< FileStorage > &fs, const String &name) const |
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| Algorithm () |
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virtual | ~Algorithm () |
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virtual void | clear () |
| Clears the algorithm state. More...
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virtual void | save (const String &filename) const |
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void | write (FileStorage &fs, const String &name) const |
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void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
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static Ptr< MSER > | create (int delta=5, int min_area=60, int max_area=14400, double max_variation=0.25, double min_diversity=.2, int max_evolution=200, double area_threshold=1.01, double min_margin=0.003, int edge_blur_size=5) |
| Full constructor for MSER detector. More...
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template<typename _Tp > |
static Ptr< _Tp > | load (const String &filename, const String &objname=String()) |
| Loads algorithm from the file. More...
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template<typename _Tp > |
static Ptr< _Tp > | loadFromString (const String &strModel, const String &objname=String()) |
| Loads algorithm from a String. More...
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template<typename _Tp > |
static Ptr< _Tp > | read (const FileNode &fn) |
| Reads algorithm from the file node. More...
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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: [193] ; 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: [84] ; 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