Catalano.Imaging.Corners
Class FastCornersDetector
- java.lang.Object
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- Catalano.Imaging.Corners.FastCornersDetector
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- All Implemented Interfaces:
- ICornersFeatureDetector
public class FastCornersDetector extends java.lang.Object implements ICornersFeatureDetector
Features from Accelerated Segment Test (FAST) corners detector.
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Nested Class Summary
Nested Classes Modifier and Type Class and Description static classFastCornersDetector.Algorithm
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Constructor Summary
Constructors Constructor and Description FastCornersDetector()Initializes a new instance of the FastCornersDetector class.FastCornersDetector(FastCornersDetector.Algorithm algorithm)Initializes a new instance of the FastCornersDetector class.FastCornersDetector(int threshold)Initializes a new instance of the FastCornersDetector class.FastCornersDetector(int threshold, boolean suppress)Initializes a new instance of the FastCornersDetector class.FastCornersDetector(int threshold, boolean suppress, FastCornersDetector.Algorithm algorithm)Initializes a new instance of the FastCornersDetector class.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method and Description FastCornersDetector.AlgorithmgetAlgorithm()Get Fast algorithm.intgetThreshold()Get Threshold.booleanisSuppressed()Check if needs apply a non-maximum suppression algorithm on the results, to allow only maximal corners.java.util.List<FeaturePoint>ProcessImage(FastBitmap fastBitmap)Process image.voidsetAlgorithm(FastCornersDetector.Algorithm algorithm)Set Fast algorithm.voidsetSuppression(boolean suppress)Set suppression if needs apply a non-maximum suppression algorithm on the results, to allow only maximal corners.voidsetThreshold(int threshold)Set Threshold.
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Constructor Detail
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FastCornersDetector
public FastCornersDetector()
Initializes a new instance of the FastCornersDetector class.
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FastCornersDetector
public FastCornersDetector(int threshold)
Initializes a new instance of the FastCornersDetector class.- Parameters:
threshold- Threshold.
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FastCornersDetector
public FastCornersDetector(FastCornersDetector.Algorithm algorithm)
Initializes a new instance of the FastCornersDetector class.- Parameters:
algorithm- Algorithm.
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FastCornersDetector
public FastCornersDetector(int threshold, boolean suppress)Initializes a new instance of the FastCornersDetector class.- Parameters:
threshold- Threshold.suppress- Supress.
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FastCornersDetector
public FastCornersDetector(int threshold, boolean suppress, FastCornersDetector.Algorithm algorithm)Initializes a new instance of the FastCornersDetector class.- Parameters:
threshold- Threshold.suppress- Supress.algorithm- Algorithm.
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Method Detail
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getThreshold
public int getThreshold()
Get Threshold. A number denoting how much brighter or darker the pixels surrounding the pixel in question should be in order to be considered a corner.- Returns:
- Threshold.
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setThreshold
public void setThreshold(int threshold)
Set Threshold. A number denoting how much brighter or darker the pixels surrounding the pixel in question should be in order to be considered a corner.- Parameters:
threshold- Threshold.
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isSuppressed
public boolean isSuppressed()
Check if needs apply a non-maximum suppression algorithm on the results, to allow only maximal corners.- Returns:
- If true, allow only maximal corners, otherwise false.
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setSuppression
public void setSuppression(boolean suppress)
Set suppression if needs apply a non-maximum suppression algorithm on the results, to allow only maximal corners.- Parameters:
suppress- If true, allow only maximal corners, otherwise false.
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getAlgorithm
public FastCornersDetector.Algorithm getAlgorithm()
Get Fast algorithm.- Returns:
- Fast algorithm.
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setAlgorithm
public void setAlgorithm(FastCornersDetector.Algorithm algorithm)
Set Fast algorithm.- Parameters:
algorithm- Fast algorithm.
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ProcessImage
public java.util.List<FeaturePoint> ProcessImage(FastBitmap fastBitmap)
Description copied from interface:ICornersFeatureDetectorProcess image.- Specified by:
ProcessImagein interfaceICornersFeatureDetector- Parameters:
fastBitmap- Image to be processed- Returns:
- List of feature points.
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