diplib/segmentation.h file

Functions for segmentation and binarization. See Segmentation.

Contents

Classes

struct dip::PerObjectEllipsoidFitParameters
Defines the parameters for the PerObjectEllipsoidFit function. more...

Functions

auto dip::BackgroundThreshold(dip::Image const& in, dip::Image const& mask, dip::Image& out, dip::dfloat distance = 2.0, dip::dfloat sigma = 4.0) -> dip::dfloat
Thresholds the image in using the unimodal background-symmetry method, and the histogram of in. more...
void dip::Canny(dip::Image const& in, dip::Image& out, dip::FloatArray const& sigmas = {1}, dip::dfloat lower = 0.5, dip::dfloat upper = 0.9, dip::String const& selection = S::ALL)
Detect edges in the grey-value image by finding salient ridges in the gradient magnitude more...
void dip::FixedThreshold(dip::Image const& in, dip::Image& out, dip::dfloat threshold, dip::dfloat foreground = 1.0, dip::dfloat background = 0.0, dip::String const& output = S::BINARY)
Thresholds an image at the threshold value. more...
auto dip::GaussianMixtureModelThreshold(dip::Image const& in, dip::Image const& mask, dip::Image& out, dip::uint nThresholds = 1) -> dip::FloatArray
Thresholds the image in using nThresholds thresholds, determined by fitting a Gaussian Mixture Model to the histogram of in. more...
void dip::GraphCut(dip::Image const& in, dip::Image const& markers, dip::Image& out, dip::dfloat sigma = 30.0, dip::dfloat lambda = 1.0, dip::dfloat gamma = 0.0)
Graph-cut segmentation more...
void dip::HysteresisThreshold(dip::Image const& in, dip::Image& out, dip::dfloat lowThreshold, dip::dfloat highThreshold)
Hysteresis threshold. more...
auto dip::IsodataThreshold(dip::Image const& in, dip::Image const& mask, dip::Image& out, dip::uint nThresholds = 1) -> dip::FloatArray
Thresholds the image in using nThresholds thresholds, determined using the Isodata algorithm (k-means clustering), and the histogram of in. more...
auto dip::KMeansClustering(dip::Image const& in, dip::Image& out, dip::Random& random, dip::uint nClusters = 2) -> dip::CoordinateArray
Applies k-means clustering to an image, yielding nClusters labeled regions. more...
auto dip::KMeansClustering(dip::Image const& in, dip::Image& out, dip::uint nClusters = 2) -> dip::CoordinateArray
Like above, using a default-initialized dip::Random object.
auto dip::MinimumErrorThreshold(dip::Image const& in, dip::Image const& mask, dip::Image& out) -> dip::dfloat
Thresholds the image in using the minimal error method by Kittler and Illingworth, and the histogram of in. more...
auto dip::MinimumVariancePartitioning(dip::Image const& in, dip::Image& out, dip::uint nClusters = 2) -> dip::CoordinateArray
Spatially partitions an image into nClusters partitions iteratively, minimizing the variance of the partitions. more...
void dip::MultipleThresholds(dip::Image const& in, dip::Image& out, dip::FloatArray const& thresholds)
Thresholds an image at multiple values, yielding a labeled image. more...
auto dip::OtsuThreshold(dip::Image const& in, dip::Image const& mask, dip::Image& out) -> dip::dfloat
Thresholds the image in using the maximal inter-class variance method by Otsu, and the histogram of in. more...
void dip::PerObjectEllipsoidFit(dip::Image const& in, dip::Image& out, dip::PerObjectEllipsoidFitParameters const& parameters)
Finds a per-object threshold such that found objects are maximally ellipsoidal. more...
void dip::RangeThreshold(dip::Image const& in, dip::Image& out, dip::dfloat lowerBound, dip::dfloat upperBound, dip::String const& output = S::BINARY, dip::dfloat foreground = 1.0, dip::dfloat background = 0.0)
Thresholds an image at two values, equivalent to lowerBound <= in && in <= upperBound. more...
void dip::Superpixels(dip::Image const& in, dip::Image& out, dip::Random& random, dip::dfloat density = 0.005, dip::dfloat compactness = 1.0, dip::String const& method = S::CW, dip::StringSet const& flags = {})
Generates superpixels (oversegmentation) more...
void dip::Superpixels(dip::Image const& in, dip::Image& out, dip::dfloat density = 0.005, dip::dfloat compactness = 1.0, dip::String const& method = S::CW, dip::StringSet const& flags = {})
Like above, using a default-initialized dip::Random object.
auto dip::Threshold(dip::Image const& in, dip::Image const& mask, dip::Image& out, dip::String const& method = S::OTSU, dip::dfloat parameter = infinity) -> dip::dfloat
Automated threshold using method. more...
auto dip::TriangleThreshold(dip::Image const& in, dip::Image const& mask, dip::Image& out, dip::dfloat sigma = 4.0) -> dip::dfloat
Thresholds the image in using the chord method (a.k.a. skewed bi-modality, maximum distance to triangle), and the histogram of in. more...
auto dip::VolumeThreshold(dip::Image const& in, dip::Image const& mask, dip::Image& out, dip::dfloat volumeFraction = 0.5) -> dip::dfloat
Thresholds an image such that a fraction volumeFraction of pixels is foreground. more...