skimage2.feature.CENSURE

class skimage2.feature.CENSURE(min_scale=1, max_scale=7, mode='DoB', non_max_threshold=0.15, line_threshold=10)

Bases: FeatureDetector

CENSURE keypoint detector.

min_scaleint, optional

Minimum scale to extract keypoints from.

max_scaleint, optional

Maximum scale to extract keypoints from. The keypoints will be extracted from all the scales except the first and the last i.e. from the scales in the range [min_scale + 1, max_scale - 1]. The filter sizes for different scales is such that the two adjacent scales comprise of an octave.

mode{‘DoB’, ‘Octagon’, ‘STAR’}, optional

Type of bi-level filter used to get the scales of the input image. Possible values are ‘DoB’, ‘Octagon’ and ‘STAR’. The three modes represent the shape of the bi-level filters i.e. box(square), octagon and star respectively. For instance, a bi-level octagon filter consists of a smaller inner octagon and a larger outer octagon with the filter weights being uniformly negative in both the inner octagon while uniformly positive in the difference region. Use STAR and Octagon for better features and DoB for better performance.

non_max_thresholdfloat, optional

Threshold value used to suppress maximas and minimas with a weak magnitude response obtained after Non-Maximal Suppression.

line_thresholdfloat, optional

Threshold for rejecting interest points which have ratio of principal curvatures greater than this value.

Attributes:

keypointsndarray of shape (N, 2)

Keypoint coordinates as (row, col).

scalesndarray of shape (N,)

Corresponding scales.

References

[1]

Motilal Agrawal, Kurt Konolige and Morten Rufus Blas “CENSURE: Center Surround Extremas for Realtime Feature Detection and Matching”, https://link.springer.com/chapter/10.1007/978-3-540-88693-8_8 DOI:10.1007/978-3-540-88693-8_8

[2]

Adam Schmidt, Marek Kraft, Michal Fularz and Zuzanna Domagala “Comparative Assessment of Point Feature Detectors and Descriptors in the Context of Robot Navigation” http://yadda.icm.edu.pl/yadda/element/bwmeta1.element.baztech-268aaf28-0faf-4872-a4df-7e2e61cb364c/c/Schmidt_comparative.pdf DOI:10.1.1.465.1117

Examples

>>> from _skimage2.data import astronaut
>>> from _skimage2.color import rgb2gray
>>> from _skimage2.feature import CENSURE
>>> img = rgb2gray(astronaut()[100:300, 100:300])
>>> censure = CENSURE()
>>> censure.detect(img)
>>> censure.keypoints
array([[  4, 148],
       [ 12,  73],
       [ 21, 176],
       [ 91,  22],
       [ 93,  56],
       [ 94,  22],
       [ 95,  54],
       [100,  51],
       [103,  51],
       [106,  67],
       [108,  15],
       [117,  20],
       [122,  60],
       [125,  37],
       [129,  37],
       [133,  76],
       [145,  44],
       [146,  94],
       [150, 114],
       [153,  33],
       [154, 156],
       [155, 151],
       [184,  63]])
>>> censure.scales
array([2, 6, 6, 2, 4, 3, 2, 3, 2, 6, 3, 2, 2, 3, 2, 2, 2, 3, 2, 2, 4, 2,
       2])

__init__(min_scale=1, max_scale=7, mode='DoB', non_max_threshold=0.15, line_threshold=10)

detect(image)

Detect CENSURE keypoints along with the corresponding scale.

Parameters:

image2D ndarray

Input image.