Image Statistics

Extracts tabular data from an image using one of a selection of algorithms. The implemented filters are to a large extent based on scikit-image, but some filters are not from this package.

Documentation

Algorithms

blob, DoG

Detects blobs in a grayscale image using the Difference of Gaussians (DoG) method. Returns table with X,Y positions and the standard deviation of the gaussian kernel that detected each blob. Operates only on first channel of image. The radius of each blob is approximately sqrt(2) sigma. Operates only on first channel of image

min sigma

Minimum standard deviation for Gaussian kernels. Keep low to detect smaller blobs (default 1)

max sigma

Maximum standard deviation for Gaussian kernels. Keep high to detect larger blobs (default 50)

sigma_ratio

The ratio between the standard deviation of Gaussian Kernels used for computing the Difference of Gaussians (default 1.6)

threshold

The absolute lower bound for scale space maxima. Local maxima smaller than thresh are ignored. Reduce this to detect blobs with less intensities. (default 2.0)

overlap

A value between 0 and 1. If the area of two blobs overlaps by a fraction greater than threshold, the smaller blob is eliminated. (default 0.5)

blob, DoH

Detects blobs in a grayscale image using the Determinant of Hessian (DoH) method. Returns table with X,Y positions and the standard deviation of the gaussian kernel used for the hessian matrix which detected each blob. The radius of each blob is approximately sigma. Operates only on first channel of image

min sigma

Minimum standard deviation for Gaussian kernels. Keep low to detect smaller blobs (default 1)

max sigma

Maximum standard deviation for Gaussian kernels. Keep high to detect larger blobs (default 50)

num sigma

The number of intermediate values for Sigma to consider (default 10)

threshold

The absolute lower bound for scale space maxima. Local maxima smaller than thresh are ignored. Reduce this to detect blobs with less intensities. (default 0.01)

overlap

A value between 0 and 1. If the area of two blobs overlaps by a fraction greater than threshold, the smaller blob is eliminated. (default 0.5)

log scale

If true then interpolation of intermediate values for Sigma are interpolated in a logrithmic scale, otherwise linear interpolation is used

blob, LoG

Detects blobs in a grayscale image using the Laplacian of Gaussian method. Returns table with X,Y positions and the standard deviation of the gaussian kernel used for detecting each blob. The radius of each blob is approximately sqrt(2) sigma. Operates only on first channel of image

min sigma

Minimum standard deviation for Gaussian kernels. Keep low to detect smaller blobs (default 1)

max sigma

Maximum standard deviation for Gaussian kernels. Keep high to detect larger blobs (default 50)

num sigma

The number of intermediate values for Sigma to consider (default 10)

threshold

The absolute lower bound for scale space maxima. Local maxima smaller than thresh are ignored. Reduce this to detect blobs with less intensities. (default 0.2)

overlap

A value between 0 and 1. If the area of two blobs overlaps by a fraction greater than threshold, the smaller blob is eliminated. (default 0.5)

log scale

If true then interpolation of intermediate values for Sigma are interpolated in a logrithmic scale, otherwise linear interpolation is used

cdf

Computes the cumulative distribution function (cdf) over all pixels. Returns cdf value and bin-center for a number of bins. Processes each channel separately and returns separate columns

bins

Number of bins for processing

features, CENSURE+DAISY

Combines the CENSUR keypoint detector with a DAISY feature extractor at the detected keypoints – picking the closest DAISY feature if non are at the exact keypoint locations

step

DAISY: Distance between descriptor samples (default 4)

radius

DAISY: Radius of the outermost ring (default 15)

rings

DAISY: Number of rings (default 3)

histograms

DAISY: Number of histograms per ring (default 8)

orientations

DAISY: Orientations per histogram (default 8)

daisy normalization

DAISY: Method for normalizing descriptors

min scale

CENSURE: Minimum scale to extract keypoints from.

max scale

CENSURE: Maximum scale to extract keypoints from. The keypoints will be extracted from all the scales except the first and the last i.e. from the scales in the range [min_scale + 1, max_scale - 1]. The filter sizes for different scales is such that the two adjacent scales comprise of an octave.

non max threshold

CENSURE: Threshold value for maximas and minimas with a weak magnitude response obtained after Non-Maximal Suppression.

line threshold

CENSURE: Threshold for interest points which have ratio of principal curvatures greater than this value.

features, daisy

Extracts all (densely) DAISY features into a table. DAISY is a feature descriptor similar to SIFT formulated in a way that allows for fast dense extraction. Typically, this is practical for bag-of-features image representations. Operates only on first channel of image

step

Distance between descriptor sampling points (default 4)

radius

Radius in pixels of the outermost ring (default 15)

rings

Number of rings (default 3)

histograms

Number of histograms sampled per ring (default 8)

orientations

Number of orientations per histogram (default 8)

daisy normalization

Method for normalizing descriptors

features, orb

Oriented FAST and rotated BRIEF feature detector and binary descriptor extractor.

N

Number of keypoints to be returned. The best N keypoints will be returned, or all found keypoints if fewer.

fast threshold

The threshold parameter in feature.corner_fast. Decrease the threshold when more corners are desired (0.08)

fast n

The n parameter in skimage.feature.corner_fast (9)

harris k

The k parameter in skimage.feature.corner_harris. Sensitivity factor to separate corners from edges. (0.04)

downscale

Downscale factor for the image pyramid (1.2)

features, probabilistic hough lines

Return lines from a progressive probabilistic line Hough transform.

threshold

Threshold for hough accumulators

line length

Minimum accepted length of detected lines. Increase parameter to extract only longer lines

line gap

Maximum gap between pixels to still form a line. Increase the parameter to merge broken lines more aggresively.

min theta

Minium angle in radians for lines, default -pi/2

max theta

Maximum angle in radians for lines, default +pi/2

num theta

Number of theta samples in the given range

histogram

Computes the histogram over all pixels. Returns histogram count and bin-center for a number of bins. Processes each channel separately and returns separate columns

bins

Number of bins for processing

min value

Lower end of range for bins

max value

Upper end of range for bins

keypoints, CENSURE

CENSURE keypoint detector.

min scale

Minimum scale to extract keypoints from.

max scale

Maximum scale to extract keypoints from. The keypoints will be extracted from all the scales except the first and the last i.e. from the scales in the range [min_scale + 1, max_scale - 1]. The filter sizes for different scales is such that the two adjacent scales comprise of an octave.

non max threshold

Threshold value used to suppress maximas and minimas with a weak magnitude response obtained after Non-Maximal Suppression.

line threshold

Threshold for rejecting interest points which have ratio of principal curvatures greater than this value.

meta

Returns meta information about image: width, height, channels, min_value, max_value, sum

prefix

Prefix added before column names

peaks, corners

Gives a table with coordinates of corners in a corner measure response image. Suppresses multiple connected peaks with same accumulator value. Operates only on first channel of image

threshold

Threshold for minimum intenstity of peaks expressed as fraction of image maximum (default 0.1)

min distance

Minimum distance between two corners

peaks, local max

Gives a table with coordinates of the peaks in an image Peaks are local maxima in a region defined by “min distance”. Operates only on first channel of image

threshold

Threshold for minimum intenstity of peaks expressed as absolute values (default 0)

min distance

Minimum distance between two corners

threshold relative

Threshold for minimum intenstity of peaks expressed as fraction of image maximum (default 0)

Definition

Input ports

source image

Image to extract statistics from

Output ports

result table

Table with results

Configuration

N (N)

(no description)

Algorithm (algorithm)

(no description)

bins (bins)

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censure mode (censure mode)

(no description)

daisy normalization (daisy normalization)

(no description)

downscale (downscale)

(no description)

fast n (fast n)

(no description)

fast threshold (fast threshold)

(no description)

harris k (harris k)

(no description)

histograms (histograms)

(no description)

line gap (line gap)

(no description)

line length (line length)

(no description)

line threshold (line threshold)

(no description)

log scale (log scale)

(no description)

max scale (max scale)

(no description)

max sigma (max sigma)

(no description)

max theta (max theta)

(no description)

max value (max value)

(no description)

min distance (min distance)

(no description)

min scale (min scale)

(no description)

min sigma (min sigma)

(no description)

min theta (min theta)

(no description)

min value (min value)

(no description)

non max threshold (non max threshold)

(no description)

num sigma (num sigma)

(no description)

num theta (num theta)

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orientations (orientations)

(no description)

overlap (overlap)

(no description)

prefix (prefix)

(no description)

radius (radius)

(no description)

rings (rings)

(no description)

sigma_ratio (sigma_ratio)

(no description)

step (step)

(no description)

threshold (threshold)

(no description)

threshold relative (threshold relative)

(no description)

Implementation

class node_imagestatistics.ImageStatistics