FloatArray2DMOPS (Fiji Javadocs 0-SNAPSHOT API)

java.lang.Object
- mpicbg.imagefeatures.FloatArray2DFeatureTransform<FloatArray2DMOPS.Param>
- - mpicbg.imagefeatures.FloatArray2DMOPS

public class FloatArray2DMOPS
extends FloatArray2DFeatureTransform<FloatArray2DMOPS.Param>

This implementation actually uses the DoG-detector as described by \cite{Lowe04} and extracts local intensity patches from coarser scales similar to what was described by \cite{BrownAl05} as Multi-Scale Oriented Patches. The intensities of the patches are enhanced such that each patch uses the full [0.0--1.0] range. BibTeX:

 @inproceedings{BrownAl05,
   author    = {Matthew Brown and Richard Szeliski and Simon Winder},
   title     = {Multi-Image Matching Using Multi-Scale Oriented Patches},
   booktitle = {CVPR '05: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1},
   year      = {2005},
   isbn      = {0-7695-2372-2},
   pages     = {510--517},
   publisher = {IEEE Computer Society},
   address   = {Washington, DC, USA},
   doi       = {http://dx.doi.org/10.1109/CVPR.2005.235},
   url       = {http://www.cs.ubc.ca/~mbrown/papers/cvpr05.pdf},
 }
 @article{Lowe04,
   author  = {David G. Lowe},
   title   = {Distinctive Image Features from Scale-Invariant Keypoints},
   journal = {International Journal of Computer Vision},
   year    = {2004},
   volume  = {60},
   number  = {2},
   pages   = {91--110},
 }

Author:: Stephan Saalfeld <saalfelds@janelia.hhmi.org>

Nested Class Summary

Nested Classes
Modifier and Type Class and Description

static class FloatArray2DMOPS.Param

Nested Classes
Modifier and Type	Class and Description
`static class`	`FloatArray2DMOPS.Param`

Field Summary

Fields
Modifier and Type Field and Description

FloatArray2D pattern
- Fields inherited from class mpicbg.imagefeatures.FloatArray2DFeatureTransform
  p

Fields
Modifier and Type	Field and Description
`FloatArray2D`	`pattern`

Constructor Summary

Constructors
Constructor and Description

FloatArray2DMOPS(FloatArray2DMOPS.Param p)
Constructor

Constructors
Constructor and Description
`FloatArray2DMOPS(FloatArray2DMOPS.Param p)` Constructor

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`static List<PointMatch>`	`createMatches(List<Feature> fs1, List<Feature> fs2, double max_sd, AbstractModel<?> model, double max_id, double rod)` identify corresponding features using spatial constraints
`static List<PointMatch>`	`createMatches(List<Feature> fs1, List<Feature> fs2, double rod, HashMap<Point,Feature> m1, HashMap<Point,Feature> m2)` Identify corresponding features.
`static List<PointMatch>`	`createMatches(List<Feature> fs1, List<Feature> fs2, float rod)` Identify corresponding features
`void`	`extractFeatures(Collection<Feature> features)` Detect features.
`static double[]`	`featureSizeHistogram(List<Feature> features, double min, double max, int bins)` get a histogram of feature sizes
`long`	`getFeatureObjectSize()` Returns the size in bytes of a Feature object.
`static long`	`getFeatureObjectSize(int fdsize)`
`float`	`getInitialSigma()`
`int`	`getMaxOctaveSize()`
`FloatArray2DScaleOctave`	`getOctave(int i)`
`FloatArray2DScaleOctave[]`	`getOctaves()`
`void`	`init(FloatArray2D src)` initialize the scale space as a scale pyramid having octave stubs only
`List<Feature>`	`run()` Detect features in all scale octaves.
`List<Feature>`	`run(int max_size)` Detect features in all scale octaves.
`List<Feature>`	`runOctave(int o)` detect features in the specified scale octave
`void`	`setInitialSigma(float initialSigma)`

Methods inherited from class mpicbg.imagefeatures.FloatArray2DFeatureTransform
extractFeatures

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Field Detail
  - pattern
```
public FloatArray2D pattern
```
- Constructor Detail
  - FloatArray2DMOPS
```
public FloatArray2DMOPS(FloatArray2DMOPS.Param p)
```
    Constructor
- Method Detail
  - getFeatureObjectSize
```
public long getFeatureObjectSize()
```
    Returns the size in bytes of a Feature object.
  - getFeatureObjectSize
```
public static long getFeatureObjectSize(int fdsize)
```
  - getOctaves
```
public FloatArray2DScaleOctave[] getOctaves()
```
  - getOctave
```
public FloatArray2DScaleOctave getOctave(int i)
```
  - init
```
public void init(FloatArray2D src)
```
    initialize the scale space as a scale pyramid having octave stubs only
    
    Specified by:
    
    init in class FloatArray2DFeatureTransform<FloatArray2DMOPS.Param>
    
    Parameters:
    
    src - image having a generating gaussian kernel of initial_sigma img must be a 2d-array of float values in range [0.0f, ..., 1.0f]
  - runOctave
```
public List<Feature> runOctave(int o)
```
    detect features in the specified scale octave
    
    Parameters:
    
    o - octave index
    
    Returns:
    
    detected features
  - run
```
public List<Feature> run()
```
    Detect features in all scale octaves. Note that there are O_SCALE_LD2 more octaves needed for descriptor extraction.
    
    Returns:
    
    detected features
  - run
```
public List<Feature> run(int max_size)
```
    Detect features in all scale octaves. Note that there are O_SCALE_LD2 more octaves needed for descriptor extraction.
    
    Returns:
    
    detected features
  - createMatches
```
public static List<PointMatch> createMatches(List<Feature> fs1,
                                             List<Feature> fs2,
                                             float rod)
```
    Identify corresponding features
    
    Parameters:
    
    fs1 - feature collection from set 1
    
    fs2 - feature collection from set 2
    
    rod - Ratio of distances (closest/next closest match)
    
    Returns:
    
    matches
  - createMatches
```
public static List<PointMatch> createMatches(List<Feature> fs1,
                                             List<Feature> fs2,
                                             double rod,
                                             HashMap<Point,Feature> m1,
                                             HashMap<Point,Feature> m2)
```
    Identify corresponding features. Fill a HashMap that stores the Features for each positive PointMatch.
    
    Parameters:
    
    fs1 - feature collection from set 1
    
    fs2 - feature collection from set 2
    
    rod - Ratio of distances (closest/next closest match)
    
    Returns:
    
    matches
  - createMatches
```
public static List<PointMatch> createMatches(List<Feature> fs1,
                                             List<Feature> fs2,
                                             double max_sd,
                                             AbstractModel<?> model,
                                             double max_id,
                                             double rod)
```
    identify corresponding features using spatial constraints
    
    Parameters:
    
    fs1 - feature collection from set 1 sorted by decreasing size
    
    fs2 - feature collection from set 2 sorted by decreasing size
    
    max_sd - maximal difference in size (ratio max/min)
    
    model - transformation model to be applied to fs2
    
    max_id - maximal distance in image space ($\sqrt{x^2+y^2}$)
    
    rod - Ratio of distances (closest/next closest match)
    
    Returns:
    
    matches TODO implement the spatial constraints
  - extractFeatures
```
public final void extractFeatures(Collection<Feature> features)
```
    Description copied from class: FloatArray2DFeatureTransform
    
    Detect features.
    
    Specified by:
    
    extractFeatures in class FloatArray2DFeatureTransform<FloatArray2DMOPS.Param>
    
    Parameters:
    
    features - the Collection to be filled
  - featureSizeHistogram
```
public static double[] featureSizeHistogram(List<Feature> features,
                                            double min,
                                            double max,
                                            int bins)
```
    get a histogram of feature sizes
  - getInitialSigma
```
public final float getInitialSigma()
```
  - setInitialSigma
```
public final void setInitialSigma(float initialSigma)
```
  - getMaxOctaveSize
```
public final int getMaxOctaveSize()
```

Class FloatArray2DMOPS

Nested Class Summary

Field Summary

Fields inherited from class mpicbg.imagefeatures.FloatArray2DFeatureTransform

Constructor Summary

Method Summary

Methods inherited from class mpicbg.imagefeatures.FloatArray2DFeatureTransform

Methods inherited from class java.lang.Object

Field Detail

pattern

Constructor Detail

FloatArray2DMOPS

Method Detail

getFeatureObjectSize

getFeatureObjectSize

getOctaves

getOctave

init

runOctave

run

run

createMatches

createMatches

createMatches

extractFeatures

featureSizeHistogram

getInitialSigma

setInitialSigma

getMaxOctaveSize