machinevisiontoolbox.Image.labels_MSER
- Image.labels_MSER(**kwargs)
Blob labelling using MSER
- Parameters:
kwargs – arguments passed to
MSER_create- Returns:
label image, number of regions
- Return type:
Image, int
Compute labels of connected components in the input greyscale image. Regions are sets of contiguous pixels that form stable regions across a range of threshold values.
The method returns the label image and the number of labels N, so labels lie in the range [0, N-1].The value in the label image in an integer indicating which region the corresponding input pixel belongs to. The background has label 0.
Example:
>>> from machinevisiontoolbox import Image >>> img = Image.Squares(2, 15) >>> img.print() 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 0 0 0 0 1 1 1 1 1 0 1 1 1 1 1 0 0 0 0 1 1 1 1 1 0 1 1 1 1 1 0 0 0 0 1 1 1 1 1 0 1 1 1 1 1 0 0 0 0 1 1 1 1 1 0 1 1 1 1 1 0 0 0 0 1 1 1 1 1 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 1 1 1 1 1 0 0 0 0 1 1 1 1 1 0 1 1 1 1 1 0 0 0 0 1 1 1 1 1 0 1 1 1 1 1 0 0 0 0 1 1 1 1 1 0 1 1 1 1 1 0 0 0 0 1 1 1 1 1 0 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 0 0 0 0 0 0 0 0 0 0 >>> labels, N = img.labels_MSER() >>> N 0 >>> labels.print() 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 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 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 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 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 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 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 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 0
- References:
Linear time maximally stable extremal regions, David Nistér and Henrik Stewénius, In Computer Vision–ECCV 2008, pages 183–196. Springer, 2008.
Robotics, Vision & Control for Python, Section 12.1.2.2, P. Corke, Springer 2023.
- Seealso: