From 361652cec209e8efb975af26b77bf87cbc893dda Mon Sep 17 00:00:00 2001 From: Ankit Agrawal Date: Thu, 1 Aug 2013 01:11:26 +0530 Subject: [PATCH] Added a NOTE explaining the preference of convolve over slanted integral image --- skimage/feature/censure.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/skimage/feature/censure.py b/skimage/feature/censure.py index 8b8e1ae4..d0ac94a9 100644 --- a/skimage/feature/censure.py +++ b/skimage/feature/censure.py @@ -32,12 +32,18 @@ def _get_filtered_image(image, n_scales, mode): scales[:, :, i] = filtered_image + # NOTE : For the Octagon shaped filter, we implemented and evaluated the + # slanted integral image based image filtering but the performance was + # more or less equal to image filtering using + # scipy.ndimage.filters.convolve(). Hence we have decided to use the + # later for a much cleaner implementation. elif mode == 'Octagon': # TODO : Decide the shapes of Octagon filters for scales > 7 outer_shape = [(5, 2), (5, 3), (7, 3), (9, 4), (9, 7), (13, 7), (15, 10)] inner_shape = [(3, 0), (3, 1), (3, 2), (5, 2), (5, 3), (5, 4), (5, 5)] + # for i in range(n_scales): scales[:, :, i] = convolve(image, _octagon_filter(outer_shape[i][0],