erosion skimage.morphology.erosion(image, selem=None, *args, **kwargs) [source] Return greyscale morphological erosion of an image. Morphological erosion sets a pixel at (i,j) to the minimum over all pixels in the neighborhood centered at (i,j). Erosion shrinks bright regions and enlarges dark regions. Parameters: image : ndarray Image array. selem : ndarray, optional The neighborhood expressed as an array of 1’s and 0’s. If None, use cross-shaped structuring element (connectivity=1). o

entropy skimage.filters.rank.entropy(image, selem, out=None, mask=None, shift_x=False, shift_y=False) [source] Local entropy. The entropy is computed using base 2 logarithm i.e. the filter returns the minimum number of bits needed to encode the local greylevel distribution. Parameters: image : 2-D array (uint8, uint16) Input image. selem : 2-D array The neighborhood expressed as a 2-D array of 1’s and 0’s. out : 2-D array (same dtype as input) If None, a new array is allocated. mask :

equalize skimage.filters.rank.equalize(image, selem, out=None, mask=None, shift_x=False, shift_y=False) [source] Equalize image using local histogram. Parameters: image : 2-D array (uint8, uint16) Input image. selem : 2-D array The neighborhood expressed as a 2-D array of 1’s and 0’s. out : 2-D array (same dtype as input) If None, a new array is allocated. mask : ndarray Mask array that defines (>0) area of the image included in the local neighborhood. If None, the complete image

enhance_contrast skimage.filters.rank.enhance_contrast(image, selem, out=None, mask=None, shift_x=False, shift_y=False) [source] Enhance contrast of an image. This replaces each pixel by the local maximum if the pixel greyvalue is closer to the local maximum than the local minimum. Otherwise it is replaced by the local minimum. Parameters: image : 2-D array (uint8, uint16) Input image. selem : 2-D array The neighborhood expressed as a 2-D array of 1’s and 0’s. out : 2-D array (same dtyp

enhance_contrast_percentile skimage.filters.rank.enhance_contrast_percentile(image, selem, out=None, mask=None, shift_x=False, shift_y=False, p0=0, p1=1) [source] Enhance contrast of an image. This replaces each pixel by the local maximum if the pixel greyvalue is closer to the local maximum than the local minimum. Otherwise it is replaced by the local minimum. Only greyvalues between percentiles [p0, p1] are considered in the filter. Parameters: image : 2-D array (uint8, uint16) Input ima

ellipsoid_stats skimage.draw.ellipsoid_stats(a, b, c) [source] Calculates analytical surface area and volume for ellipsoid with semimajor axes aligned with grid dimensions of specified spacing. Parameters: a : float Length of semimajor axis aligned with x-axis. b : float Length of semimajor axis aligned with y-axis. c : float Length of semimajor axis aligned with z-axis. Returns: vol : float Calculated volume of ellipsoid. surf : float Calculated surface area of ellipsoid.

EllipseModel class skimage.measure.EllipseModel [source] Bases: skimage.measure.fit.BaseModel Total least squares estimator for 2D ellipses. The functional model of the ellipse is: xt = xc + a*cos(theta)*cos(t) - b*sin(theta)*sin(t) yt = yc + a*sin(theta)*cos(t) + b*cos(theta)*sin(t) d = sqrt((x - xt)**2 + (y - yt)**2) where (xt, yt) is the closest point on the ellipse to (x, y). Thus d is the shortest distance from the point to the ellipse. This estimator minimizes the squared distances fr

ellipsoid skimage.draw.ellipsoid(a, b, c, spacing=(1.0, 1.0, 1.0), levelset=False) [source] Generates ellipsoid with semimajor axes aligned with grid dimensions on grid with specified spacing. Parameters: a : float Length of semimajor axis aligned with x-axis. b : float Length of semimajor axis aligned with y-axis. c : float Length of semimajor axis aligned with z-axis. spacing : tuple of floats, length 3 Spacing in (x, y, z) spatial dimensions. levelset : bool If True, returns the

ellipse_perimeter skimage.draw.ellipse_perimeter() Generate ellipse perimeter coordinates. Parameters: cy, cx : int Centre coordinate of ellipse. yradius, xradius : int Minor and major semi-axes. (x/xradius)**2 + (y/yradius)**2 = 1. orientation : double, optional (default 0) Major axis orientation in clockwise direction as radians. shape : tuple, optional Image shape which is used to determine the maximum extent of output pixel coordinates. This is useful for ellipses which exceed th

dtype_limits skimage.dtype_limits(image, clip_negative=True) [source] Return intensity limits, i.e. (min, max) tuple, of the image’s dtype. Parameters: image : ndarray Input image. clip_negative : bool If True, clip the negative range (i.e. return 0 for min intensity) even if the image dtype allows negative values.