corner_moravec skimage.feature.corner_moravec() Compute Moravec corner measure response image. This is one of the simplest corner detectors and is comparatively fast but has several limitations (e.g. not rotation invariant). Parameters: image : ndarray Input image. window_size : int, optional (default 1) Window size. Returns: response : ndarray Moravec response image. References [R136] http://kiwi.cs.dal.ca/~dparks/CornerDetection/moravec.htm [R137] http://en.wikipedia.org/wiki/Cor

corner_foerstner skimage.feature.corner_foerstner(image, sigma=1) [source] Compute Foerstner corner measure response image. This corner detector uses information from the auto-correlation matrix A: A = [(imx**2) (imx*imy)] = [Axx Axy] [(imx*imy) (imy**2)] [Axy Ayy] Where imx and imy are first derivatives, averaged with a gaussian filter. The corner measure is then defined as: w = det(A) / trace(A) (size of error ellipse) q = 4 * det(A) / trace(A)**2 (roundness of erro

corner_harris skimage.feature.corner_harris(image, method='k', k=0.05, eps=1e-06, sigma=1) [source] Compute Harris corner measure response image. This corner detector uses information from the auto-correlation matrix A: A = [(imx**2) (imx*imy)] = [Axx Axy] [(imx*imy) (imy**2)] [Axy Ayy] Where imx and imy are first derivatives, averaged with a gaussian filter. The corner measure is then defined as: det(A) - k * trace(A)**2 or: 2 * det(A) / (trace(A) + eps) Parameters: image : nd

corner_kitchen_rosenfeld skimage.feature.corner_kitchen_rosenfeld(image, mode='constant', cval=0) [source] Compute Kitchen and Rosenfeld corner measure response image. The corner measure is calculated as follows: (imxx * imy**2 + imyy * imx**2 - 2 * imxy * imx * imy) / (imx**2 + imy**2) Where imx and imy are the first and imxx, imxy, imyy the second derivatives. Parameters: image : ndarray Input image. mode : {‘constant’, ‘reflect’, ‘wrap’, ‘nearest’, ‘mirror’}, optional How to hand

copy_func skimage.filters.copy_func(f, name=None) [source] Create a copy of a function. Parameters: f : function Function to copy. name : str, optional Name of new function.

corner_fast skimage.feature.corner_fast(image, n=12, threshold=0.15) [source] Extract FAST corners for a given image. Parameters: image : 2D ndarray Input image. n : int Minimum number of consecutive pixels out of 16 pixels on the circle that should all be either brighter or darker w.r.t testpixel. A point c on the circle is darker w.r.t test pixel p if Ic < Ip - threshold and brighter if Ic > Ip + threshold. Also stands for the n in FAST-n corner detector. threshold : float Thre

convex_hull_object skimage.morphology.convex_hull_object(image, neighbors=8) [source] Compute the convex hull image of individual objects in a binary image. The convex hull is the set of pixels included in the smallest convex polygon that surround all white pixels in the input image. Parameters: image : (M, N) array Binary input image. neighbors : {4, 8}, int Whether to use 4- or 8-connectivity. Returns: hull : ndarray of bool Binary image with pixels in convex hull set to True. No

convex_hull_image skimage.morphology.convex_hull_image(image) [source] Compute the convex hull image of a binary image. The convex hull is the set of pixels included in the smallest convex polygon that surround all white pixels in the input image. Parameters: image : (M, N) array Binary input image. This array is cast to bool before processing. Returns: hull : (M, N) array of bool Binary image with pixels in convex hull set to True. References [R296] http://blogs.mathworks.com/steve/

convert_colorspace skimage.color.convert_colorspace(arr, fromspace, tospace) [source] Convert an image array to a new color space. Parameters: arr : array_like The image to convert. fromspace : str The color space to convert from. Valid color space strings are ['RGB', 'HSV', 'RGB CIE', 'XYZ']. Value may also be specified as lower case. tospace : str The color space to convert to. Valid color space strings are ['RGB', 'HSV', 'RGB CIE', 'XYZ']. Value may also be specified as lower case.

concatenate_images skimage.io.concatenate_images(ic) [source] Concatenate all images in the image collection into an array. Parameters: ic: an iterable of images (including ImageCollection and MultiImage) The images to be concatenated. Returns: ar : np.ndarray An array having one more dimension than the images in ic. Raises: ValueError If images in ic don’t have identical shapes. See also ImageCollection.concatenate, MultiImage.concatenate