From 279d89278901f730dbb297df67932b8e544a7b30 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Johannes=20Sch=C3=B6nberger?= Date: Wed, 22 Jan 2014 18:50:39 -0500 Subject: [PATCH] Improve BRIEF doc string --- skimage/feature/brief.py | 24 ++++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/skimage/feature/brief.py b/skimage/feature/brief.py index bba07926..3421156b 100644 --- a/skimage/feature/brief.py +++ b/skimage/feature/brief.py @@ -12,15 +12,15 @@ class BRIEF(DescriptorExtractor): """BRIEF binary descriptor extractor. BRIEF (Binary Robust Independent Elementary Features) is an efficient - feature point descriptor. It it is highly discriminative even when using - relatively few bits and can be computed using simple intensity difference + feature point descriptor. It is highly discriminative even when using + relatively few bits and is computed using simple intensity difference tests. - For each keypoint intensity comparisons are carried out for a specifically + For each keypoint, intensity comparisons are carried out for a specifically distributed number N of pixel-pairs resulting in a binary descriptor of - length N. The descriptor similarity can thus be computed using the Hamming - distance which leads to very good matching performance in contrast to the - L2 norm. + length N. For binary descriptors the Hamming distance can be used for + feature matching, which leads to lower computational cost in comparison to + the L2 norm. Parameters ---------- @@ -35,12 +35,12 @@ class BRIEF(DescriptorExtractor): around keypoints. sample_seed : int, optional Seed for the random sampling of the decision pixel-pairs. From a square - window with length patch_size, pixel pairs are sampled using the `mode` - parameter to build the descriptors using intensity comparison. The - value of `sample_seed` must be the same for the images to be matched - while building the descriptors. + window with length `patch_size`, pixel pairs are sampled using the + `mode` parameter to build the descriptors using intensity comparison. + The value of `sample_seed` must be the same for the images to be + matched while building the descriptors. sigma : float, optional - Standard deviation of the Gaussian low pass filter applied to the image + Standard deviation of the Gaussian low-pass filter applied to the image to alleviate noise sensitivity, which is strongly recommended to obtain discriminative and good descriptors. @@ -139,7 +139,7 @@ class BRIEF(DescriptorExtractor): image = _prepare_grayscale_input_2D(image) - # Gaussian Low pass filtering to alleviate noise sensitivity + # Gaussian low-pass filtering to alleviate noise sensitivity image = np.ascontiguousarray(gaussian_filter(image, self.sigma)) # Sampling pairs of decision pixels in patch_size x patch_size window