Superpixels

“My research areas include computer vision and computer graphics. My particular interests are in using vision to automatically build 3-D models from images, computational photography, and image-based rendering…”
Richard Szeliski

Preliminaries

import matplotlib.pyplot as plt
from skimage.segmentation import slic
from skimage.segmentation import mark_boundaries
from skimage.util import img_as_float
from skimage import io

%pylab inline
%matplotlib inline 

Populating the interactive namespace from numpy and matplotlib

Input image

img = img_as_float(io.imread('/home/cobalt/Pictures/frances2.jpg'))
io.imshow(img);

_config.yml

Oversegmentation to produce the Superpixels

for segs in (10, 50, 100, 300, 500, 1000):
    segments = slic(img, n_segments = segs, sigma = 4)
    fig = plt.figure(figsize=(12,4))
    ax = fig.add_axes([0, 0, 1, 1])
    ax.imshow(mark_boundaries(img, segments)) 
plt.show()

_config.yml

_config.yml

_config.yml

_config.yml

_config.yml

_config.yml

By: Melvin Cabatuan melvincabatuan@gmail.com

This ipython notebook is licensed under the CC-BY-NC-SA license: http://creativecommons.org/licenses/by-nc-sa/4.0/

http://i.creativecommons.org/l/by-nc-sa/3.0/88x31.png

References:

[1.] Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine Süsstrunk, SLIC Superpixels Compared to State-of-the-art Superpixel Methods, TPAMI, May 2012.
[2.] Adrian Rosebrock, Segmentation: A SLIC Superpixel Tutorial using Python. http://www.pyimagesearch.com/2014/07/28/a-slic-superpixel-tutorial-using-python
[3.] http://ivrg.epfl.ch/research/superpixels#SLICO
[4.] http://scikit-image.org/docs/dev/api/skimage.segmentation.html#skimage.segmentation.slic
Written on March 28, 2015