diff --git a/skimage/segmentation/boundaries.py b/skimage/segmentation/boundaries.py index 11773b1c..37fd77fd 100644 --- a/skimage/segmentation/boundaries.py +++ b/skimage/segmentation/boundaries.py @@ -6,7 +6,7 @@ from ..color import gray2rgb from .._shared.utils import deprecated -def find_boundaries(label_img, connectivity=1): +def find_boundaries(label_img, connectivity=1, mode='thick', background=0): """Return bool array where boundaries between labeled regions are True. Parameters @@ -21,15 +21,116 @@ def find_boundaries(label_img, connectivity=1): pixels sharing an edge (in 2D) or a face (in 3D) will be considered neighbors. A connectivity of `label_img.ndim` means pixels sharing a corner will be considered neighbors. + mode: string in {'thick', 'inner', 'outer', 'subpixel'} + How to mark the boundaries: + + - thick: any pixel not completely surrounded by pixels of the + same label (defined by `connectivity`) is marked as a boundary. + This results in boundaries that are 2 pixels thick. + - inner: outline the pixels *just inside* of objects, leaving + background pixels untouched. + - outer: outline pixels in the background around object + boundaries. When two objects touch, their boundary is also + marked. + - subpixel: return a doubled image, with pixels *between* the + original pixels marked as boundary where appropriate. + background: int, optional + For modes 'inner' and 'outer', a definition of a background + label is required. See `mode` for descriptions of these two. Returns ------- boundaries : array of bool, same shape as `label_img` - A bool image where `True` represents a boundary pixel. + A bool image where ``True`` represents a boundary pixel. For + `mode` equal to 'subpixel', ``boundaries.shape[i]`` is equal + to ``2 * label_img.shape[i] - 1`` for all ``i`` (a pixel is + inserted in between all other pairs of pixels). + + Examples + -------- + >>> labels = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], + ... [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], + ... [0, 0, 0, 0, 0, 5, 5, 5, 0, 0], + ... [0, 0, 1, 1, 1, 5, 5, 5, 0, 0], + ... [0, 0, 1, 1, 1, 5, 5, 5, 0, 0], + ... [0, 0, 1, 1, 1, 5, 5, 5, 0, 0], + ... [0, 0, 0, 0, 0, 5, 5, 5, 0, 0], + ... [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], + ... [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.uint8) + >>> find_boundaries(labels).astype(np.uint8) # display 1/0, not True/False + array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 1, 1, 1, 0, 0], + [0, 0, 1, 1, 1, 1, 1, 1, 1, 0], + [0, 1, 1, 1, 1, 1, 0, 1, 1, 0], + [0, 1, 1, 0, 1, 1, 0, 1, 1, 0], + [0, 1, 1, 1, 1, 1, 0, 1, 1, 0], + [0, 0, 1, 1, 1, 1, 1, 1, 1, 0], + [0, 0, 0, 0, 0, 1, 1, 1, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=uint8) + >>> find_boundaries(labels, mode='inner').astype(np.uint8) + array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 1, 1, 1, 0, 0], + [0, 0, 1, 1, 1, 1, 0, 1, 0, 0], + [0, 0, 1, 0, 1, 1, 0, 1, 0, 0], + [0, 0, 1, 1, 1, 1, 0, 1, 0, 0], + [0, 0, 0, 0, 0, 1, 1, 1, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=uint8) + >>> find_boundaries(labels, mode='outer').astype(np.uint8) + array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 1, 1, 1, 0, 0], + [0, 0, 1, 1, 1, 1, 0, 0, 1, 0], + [0, 1, 0, 0, 1, 1, 0, 0, 1, 0], + [0, 1, 0, 0, 1, 1, 0, 0, 1, 0], + [0, 1, 0, 0, 1, 1, 0, 0, 1, 0], + [0, 0, 1, 1, 1, 1, 0, 0, 1, 0], + [0, 0, 0, 0, 0, 1, 1, 1, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=uint8) + >>> find_boundaries(labels, mode='subpixel').astype(np.uint8) + array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0], + [0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0], + [0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0], + [0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0], + [0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0], + [0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0], + [0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0], + [0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0], + [0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0], + [0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0], + [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=uint8) """ - selem = nd.generate_binary_structure(label_img.ndim, connectivity) - boundaries = dilation(label_img, selem) != erosion(label_img, selem) - return boundaries + ndim = label_img.ndim + selem = nd.generate_binary_structure(ndim, connectivity) + if mode != 'subpixel': + boundaries = dilation(label_img, selem) != erosion(label_img, selem) + if mode == 'inner': + foreground_image = (label_img != background) + boundaries &= foreground_image + elif mode == 'outer': + background_image = (label_img == background) + selem = nd.generate_binary_structure(ndim, ndim) + no_adjacent_background = ~dilation(background_image, selem) + boundaries &= (background_image | no_adjacent_background) + return boundaries + else: + label_img_expanded = np.zeros([(2 * s - 1) for s in label_img.shape], + label_img.dtype) + pixels = [slice(None, None, 2)] * ndim + selem = nd.generate_binary_structure(ndim, ndim) + label_img_expanded[pixels] = label_img + max_label = np.iinfo(label_img.dtype).max + label_img_edge_inverted = np.array(label_img_expanded, copy=True) + label_img_edge_inverted[label_img_expanded == 0] = max_label + boundaries = (dilation(label_img_expanded, selem) != + erosion(label_img_edge_inverted, selem)) + return boundaries def mark_boundaries(image, label_img, color=(1, 1, 0),