java.lang.Object

boofcv.alg.filter.binary.GThresholdImageOps

public class GThresholdImageOps extends Object

Weakly typed version of ThresholdImageOps.

Constructor Summary

Constructors

Constructor

Description

GThresholdImageOps()
Method Summary

Modifier and Type

Method

Description

static <T extends ImageGray<T>> GrayU8

blockMean(T input, @Nullable GrayU8 output, ConfigLength width, double scale, boolean down)

Applies a threshold to an image by computing the mean values in a regular grid across the input image.

static <T extends ImageGray<T>> GrayU8

blockMinMax(T input, @Nullable GrayU8 output, ConfigLength width, double scale, boolean down, double textureThreshold)

Applies a threshold to an image by computing the min and max values in a regular grid across the input image.

static <T extends ImageGray<T>> GrayU8

blockOtsu(T input, @Nullable GrayU8 output, boolean otsu2, ConfigLength width, double tuning, double scale, boolean down)

Applies a threshold to an image by computing the Otsu threshold in a regular grid across the input image.

static int

computeEntropy(int[] histogram, int length, int totalPixels)

Computes a threshold which maximizes the entropy between the foreground and background regions.

static double

computeEntropy(ImageGray input, double minValue, double maxValue)

Computes a threshold which maximizes the entropy between the foreground and background regions.

static int

computeHuang(int[] histogram, int length)

Implements Huang's fuzzy thresholding method Uses Shannon's entropy function (one can also use Yager's entropy function) Huang L.-K.

static double

computeHuang(ImageGray input, double minValue, double maxValue)

Computes Huang's Minimum fyzzy thresholding from an input image.

static int

computeLi(int[] histogram, int length)

Implements Li's Minimum Cross Entropy thresholding method This implementation is based on the iterative version (Ref.

static double

computeLi(ImageGray input, double minValue, double maxValue)

Computes Li's Minimum Cross Entropy thresholding from an input image.

static int

computeOtsu(int[] histogram, int length, int totalPixels)

Computes the variance based Otsu threshold from a histogram directly.

static double

computeOtsu(ImageGray input, double minValue, double maxValue)

Computes the variance based threshold using Otsu's method from an input image.

static int

computeOtsu2(int[] histogram, int length, int totalPixels)

Computes a modified modified Otsu threshold which maximizes the distance from the distributions means.

static int

computeOtsu2(ImageGray input, int minValue, int maxValue)

Computes the variance based threshold using a modified Otsu method from an input image.

static <T extends ImageGray<T>> GrayU8

localGaussian(T input, @Nullable GrayU8 output, ConfigLength width, double scale, boolean down, T work1, @Nullable ImageGray work2)

Thresholds the image using a locally adaptive threshold that is computed using a local square region centered on each pixel.

static <T extends ImageGray<T>> GrayU8

localMean(T input, GrayU8 output, ConfigLength width, double scale, boolean down, T work1, T work2, @Nullable GrowArray work3)

Thresholds the image using a locally adaptive threshold that is computed using a local square region centered on each pixel.

static <T extends ImageGray<T>> GrayU8

localNiblack(T input, @Nullable GrayU8 output, ConfigLength width, float k, boolean down)

Applies Niblack thresholding to the input image.

static <T extends ImageGray<T>> GrayU8

localNick(T input, @Nullable GrayU8 output, ConfigLength width, float k, boolean down)

Applies NICK thresholding to the input image.

static <T extends ImageGray<T>> GrayU8

localOtsu(T input, @Nullable GrayU8 output, boolean otsu2, ConfigLength width, double tuning, double scale, boolean down)

FactoryThresholdBinary.localOtsu(ConfigLength, double, boolean, boolean, double, Class)

static <T extends ImageGray<T>> GrayU8

localSauvola(T input, @Nullable GrayU8 output, ConfigLength width, float k, boolean down)

Applies Sauvola thresholding to the input image.

static <T extends ImageGray<T>> GrayU8

localWolf(T input, @Nullable GrayU8 output, ConfigLength width, float k, boolean down)

Applies Wolf thresholding to the input image.

protected static <T extends ImageGray<T>> GrayU8

niblackFamily(T input, @Nullable GrayU8 output, ConfigLength width, float k, boolean down, ThresholdNiblackFamily.Variant variant)

static <T extends ImageGray<T>> GrayU8

threshold(T input, @Nullable GrayU8 output, double threshold, boolean down)

Applies a global threshold across the whole image.

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

Constructor Details
- GThresholdImageOps
  
  public GThresholdImageOps()
Method Details
- computeOtsu
  
  public static double computeOtsu(ImageGray input, double minValue, double maxValue)
  
  Computes the variance based threshold using Otsu's method from an input image. Internally it uses computeOtsu(int[], int, int) and GImageStatistics.histogram(ImageGray, double, int[])
  
  Parameters:
  
  input - Input gray-scale image
  
  minValue - The minimum value of a pixel in the image. (inclusive)
  
  maxValue - The maximum value of a pixel in the image. (inclusive)
  
  Returns:
  
  Selected threshold.
- computeOtsu2
  
  public static int computeOtsu2(ImageGray input, int minValue, int maxValue)
  
  Computes the variance based threshold using a modified Otsu method from an input image. Internally it uses computeOtsu2(int[], int, int) and GImageStatistics.histogram(ImageGray, double, int[])
  
  Parameters:
  
  input - Input gray-scale image
  
  minValue - The minimum value of a pixel in the image. (inclusive)
  
  maxValue - The maximum value of a pixel in the image. (inclusive)
  
  Returns:
  
  Selected threshold.
- computeOtsu
  
  public static int computeOtsu(int[] histogram, int length, int totalPixels)
  
  Computes the variance based Otsu threshold from a histogram directly. The threshold is selected by minimizing the spread of both foreground and background pixel values.
  
  Parameters:
  
  histogram - Histogram of pixel intensities.
  
  length - Number of elements in the histogram.
  
  totalPixels - Total pixels in the image
  
  Returns:
  
  Selected threshold
- computeOtsu2
  
  public static int computeOtsu2(int[] histogram, int length, int totalPixels)
  
  Computes a modified modified Otsu threshold which maximizes the distance from the distributions means. In extremely sparse histograms with the values clustered at the two means Otsu will select a threshold which is at the lower peak and in binary data this can cause a total failure.
  
  Parameters:
  
  histogram - Histogram of pixel intensities.
  
  length - Number of elements in the histogram.
  
  totalPixels - Total pixels in the image
  
  Returns:
  
  Selected threshold
- computeLi
  
  public static double computeLi(ImageGray input, double minValue, double maxValue)
  
  Computes Li's Minimum Cross Entropy thresholding from an input image. Internally it uses computeLi(int[], int) and GImageStatistics.histogram(ImageGray, double, int[])
  
  Parameters:
  
  input - Input gray-scale image
  
  minValue - The minimum value of a pixel in the image. (inclusive)
  
  maxValue - The maximum value of a pixel in the image. (inclusive)
  
  Returns:
  
  Selected threshold.
- computeLi
  
  public static int computeLi(int[] histogram, int length)
  
  Implements Li's Minimum Cross Entropy thresholding method This implementation is based on the iterative version (Ref. 2) of the algorithm. 1) Li C.H. and Lee C.K. (1993) "Minimum Cross Entropy Thresholding" Pattern Recognition, 26(4): 617-625 2) Li C.H. and Tam P.K.S. (1998) "An Iterative Algorithm for Minimum Cross Entropy Thresholding"Pattern Recognition Letters, 18(8): 771-776 3) Sezgin M. and Sankur B. (2004) "Survey over Image Thresholding Techniques and Quantitative Performance Evaluation" Journal of Electronic Imaging, 13(1): 146-165 http://citeseer.ist.psu.edu/sezgin04survey.html Ported to ImageJ plugin by G.Landini from E Celebi's fourier_0.8 routines Ported from Imagej code (https://imagej.nih.gov/ij/developer/source/) to BoofCV by Nico Stuurman
  
  Parameters:
  
  histogram - Histogram of pixel intensities.
  
  length - Number of elements in the histogram.
  
  Returns:
  
  Selected threshold
- computeHuang
  
  public static double computeHuang(ImageGray input, double minValue, double maxValue)
  
  Computes Huang's Minimum fyzzy thresholding from an input image. Internally it uses computeHuang(int[], int) and GImageStatistics.histogram(ImageGray, double, int[])
  
  Parameters:
  
  input - Input gray-scale image
  
  minValue - The minimum value of a pixel in the image. (inclusive)
  
  maxValue - The maximum value of a pixel in the image. (inclusive)
  
  Returns:
  
  Selected threshold.
- computeHuang
  
  public static int computeHuang(int[] histogram, int length)
  
  Implements Huang's fuzzy thresholding method Uses Shannon's entropy function (one can also use Yager's entropy function) Huang L.-K. and Wang M.-J.J. (1995) "Image Thresholding by Minimizing the Measures of Fuzziness" Pattern Recognition, 28(1): 41-51 M. Emre Celebi 06.15.2007
  
  Ported to ImageJ plugin by G.Landini from E Celebi's fourier_0.8 routines Ported from Imagej code (https://imagej.nih.gov/ij/developer/source/) to BoofCV by Nico Stuurman
  
  Parameters:
  
  histogram - Histogram of pixel intensities.
  
  length - Number of elements in the histogram.
  
  Returns:
  
  Selected threshold
- computeEntropy
  
  public static double computeEntropy(ImageGray input, double minValue, double maxValue)
  
  Computes a threshold which maximizes the entropy between the foreground and background regions. See computeEntropy(int[], int, int) for more details.
  Parameters:
  
  input - Input gray-scale image
  
  minValue - The minimum value of a pixel in the image. (inclusive)
  
  maxValue - The maximum value of a pixel in the image. (inclusive)
  
  Returns:
  
  Selected threshold.
  
  See Also:
  
  GImageStatistics.histogram(ImageGray, double, int[])
- computeEntropy
  
  public static int computeEntropy(int[] histogram, int length, int totalPixels)
  
  Computes a threshold which maximizes the entropy between the foreground and background regions. See [1] for algorithmic details, which cites [2].
  
  [1] E.R. Davies "Machine Vision Theory Algorithms Practicalities" 3rd Ed. 2005. pg. 124
  [2] Hannah, Ian, Devesh Patel, and Roy Davies. "The use of variance and entropic thresholding methods for image segmentation." Pattern Recognition 28.8 (1995): 1135-1143.
  
  Parameters:
  
  histogram - Histogram of pixel intensities.
  
  length - Number of elements in the histogram.
  
  totalPixels - Total pixels in the image
  
  Returns:
  
  Selected threshold
- threshold
  
  public static <T extends ImageGray<T>> GrayU8 threshold(T input, @Nullable @Nullable GrayU8 output, double threshold, boolean down)
  
  Applies a global threshold across the whole image. If 'down' is true, then pixels with values ≤ to 'threshold' are set to 1 and the others set to 0. If 'down' is false, then pixels with values > to 'threshold' are set to 1 and the others set to 0.
  
  Parameters:
  
  input - Input image. Not modified.
  
  output - (Optional) Binary output image. If null a new image will be declared. Modified.
  
  threshold - threshold value.
  
  down - If true then the inequality ≤ is used, otherwise if false then > is used.
  
  Returns:
  
  binary image.
- localMean
  
  public static <T extends ImageGray<T>> GrayU8 localMean(T input, GrayU8 output, ConfigLength width, double scale, boolean down, @Nullable T work1, @Nullable T work2, @Nullable @Nullable GrowArray work3)
  
  Thresholds the image using a locally adaptive threshold that is computed using a local square region centered on each pixel. The threshold is equal to the average value of the surrounding pixels times the scale. If down is true then b(x,y) = I(x,y) ≤ T(x,y) * scale ? 1 : 0. Otherwise b(x,y) = I(x,y) > T(x,y) * scale ? 0 : 1
  
  NOTE: Internally, images are declared to store intermediate results. If more control is needed over memory call the type specific function.
  
  Parameters:
  
  input - Input image.
  
  output - (optional) Output binary image. If null it will be declared internally.
  
  width - Width of square region.
  
  scale - Scale factor used to adjust threshold
  
  down - Should it threshold up or down.
  
  work1 - (Optional) Internal workspace. Can be null
  
  work2 - (Optional) Internal workspace. Can be null
  
  Returns:
  
  binary image.
- localGaussian
  
  public static <T extends ImageGray<T>> GrayU8 localGaussian(T input, @Nullable @Nullable GrayU8 output, ConfigLength width, double scale, boolean down, @Nullable T work1, @Nullable @Nullable ImageGray work2)
  
  Thresholds the image using a locally adaptive threshold that is computed using a local square region centered on each pixel. The threshold is equal to the gaussian weighted sum of the surrounding pixels times the scale. If down is true then b(x,y) = I(x,y) ≤ T(x,y) * scale ? 1 : 0. Otherwise b(x,y) = I(x,y) > T(x,y) * scale ? 0 : 1
  
  NOTE: Internally, images are declared to store intermediate results. If more control is needed over memory call the type specific function.
  
  Parameters:
  
  input - Input image.
  
  output - (optional) Output binary image. If null it will be declared internally.
  
  width - Width of square region.
  
  scale - Scale factor used to adjust threshold
  
  down - Should it threshold up or down.
  
  work1 - (Optional) Internal workspace. Can be null
  
  work2 - (Optional) Internal workspace. Can be null
  
  Returns:
  
  binary image.
- localOtsu
  
  public static <T extends ImageGray<T>> GrayU8 localOtsu(T input, @Nullable @Nullable GrayU8 output, boolean otsu2, ConfigLength width, double tuning, double scale, boolean down)
  
  FactoryThresholdBinary.localOtsu(ConfigLength, double, boolean, boolean, double, Class)
- localNiblack
  
  public static <T extends ImageGray<T>> GrayU8 localNiblack(T input, @Nullable @Nullable GrayU8 output, ConfigLength width, float k, boolean down)
  
  Applies Niblack thresholding to the input image. Intended for use with text image.
  Parameters:
  
  input - Input image.
  
  output - (optional) Output binary image. If null it will be declared internally.
  
  width - Width of square region.
  
  k - Positive parameter used to tune threshold. Try 0.3
  
  down - Should it threshold up or down.
  
  Returns:
  
  binary image
  
  See Also:
  
  ThresholdNiblackFamily
- localSauvola
  
  public static <T extends ImageGray<T>> GrayU8 localSauvola(T input, @Nullable @Nullable GrayU8 output, ConfigLength width, float k, boolean down)
  
  Applies Sauvola thresholding to the input image. Intended for use with text image.
  Parameters:
  
  input - Input image.
  
  output - (optional) Output binary image. If null it will be declared internally.
  
  width - Width of square region.
  
  k - Positive parameter used to tune threshold. Try 0.3
  
  down - Should it threshold up or down.
  
  Returns:
  
  binary image
  
  See Also:
  
  ThresholdNiblackFamily
- localWolf
  
  public static <T extends ImageGray<T>> GrayU8 localWolf(T input, @Nullable @Nullable GrayU8 output, ConfigLength width, float k, boolean down)
  
  Applies Wolf thresholding to the input image. Intended for use with text image.
  Parameters:
  
  input - Input image.
  
  output - (optional) Output binary image. If null it will be declared internally.
  
  width - Width of square region.
  
  k - Positive parameter used to tune threshold. Try 0.3
  
  down - Should it threshold up or down.
  
  Returns:
  
  binary image
  
  See Also:
  
  ThresholdNiblackFamily
- niblackFamily
  
  protected static <T extends ImageGray<T>> GrayU8 niblackFamily(T input, @Nullable @Nullable GrayU8 output, ConfigLength width, float k, boolean down, ThresholdNiblackFamily.Variant variant)
- localNick
  
  public static <T extends ImageGray<T>> GrayU8 localNick(T input, @Nullable @Nullable GrayU8 output, ConfigLength width, float k, boolean down)
  
  Applies NICK thresholding to the input image. Intended for use with text image.
  Parameters:
  
  input - Input image.
  
  output - (optional) Output binary image. If null it will be declared internally.
  
  width - Width of square region.
  
  k - Positive parameter used to tune threshold. Try -0.1 to -0.2
  
  down - Should it threshold up or down.
  
  Returns:
  
  binary image
  
  See Also:
  
  ThresholdNick
- blockMinMax
  
  public static <T extends ImageGray<T>> GrayU8 blockMinMax(T input, @Nullable @Nullable GrayU8 output, ConfigLength width, double scale, boolean down, double textureThreshold)
  
  Applies a threshold to an image by computing the min and max values in a regular grid across the input image. See ThresholdBlockMinMax for the details.
  
  Parameters:
  
  input - Input image.
  
  output - (optional) Output binary image. If null it will be declared internally.
  
  width - Width of square region.
  
  scale - Scale factor used to adjust threshold
  
  down - Should it threshold up or down.
  
  textureThreshold - If the min and max values are within this threshold the pixel will be set to 1.
  
  Returns:
  
  Binary image
- blockMean
  
  public static <T extends ImageGray<T>> GrayU8 blockMean(T input, @Nullable @Nullable GrayU8 output, ConfigLength width, double scale, boolean down)
  
  Applies a threshold to an image by computing the mean values in a regular grid across the input image. See ThresholdBlockMean for the details.
  
  Parameters:
  
  input - Input image.
  
  output - (optional) Output binary image. If null it will be declared internally.
  
  width - Width of square region.
  
  scale - Scale factor used to adjust threshold
  
  down - Should it threshold up or down.
  
  Returns:
  
  Binary image
- blockOtsu
  
  public static <T extends ImageGray<T>> GrayU8 blockOtsu(T input, @Nullable @Nullable GrayU8 output, boolean otsu2, ConfigLength width, double tuning, double scale, boolean down)
  
  Applies a threshold to an image by computing the Otsu threshold in a regular grid across the input image. See ThresholdBlockOtsu for the details.
  
  Parameters:
  
  input - Input image.
  
  output - (optional) Output binary image. If null it will be declared internally.
  
  width - Width of square region.
  
  tuning - Tuning parameter. 0 = regular Otsu
  
  down - Should it threshold up or down.
  
  Returns:
  
  Binary image

Class GThresholdImageOps

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Details

GThresholdImageOps

Method Details

computeOtsu

computeOtsu2

computeOtsu

computeOtsu2

computeLi

computeLi

computeHuang

computeHuang

computeEntropy

computeEntropy

threshold

localMean

localGaussian

localOtsu

localNiblack

localSauvola

localWolf

niblackFamily

localNick

blockMinMax

blockMean

blockOtsu