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Ch 10 Image Segmentation. Ideally, partition an image into regions corresponding to real world objects. Goals of segmentation. Segments formed by K-means. Segmentation attempted via contour/boundary detection. Clustering versus region-growing. Clustering versus region-growing.

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ch 10 image segmentation

Ch 10 Image Segmentation

Ideally, partition an image into regions corresponding to real world objects.

CSE 803 Fall 2008 Stockman

goals of segmentation
Goals of segmentation

CSE 803 Fall 2008 Stockman

segments formed by k means
Segments formed by K-means

CSE 803 Fall 2008 Stockman

clustering versus region growing
Clustering versus region-growing

CSE 803 Fall 2008 Stockman

clustering versus region growing1
Clustering versus region-growing

CSE 803 Fall 2008 Stockman

k means clustering as before vectors can contain color texture
K-means clustering as before: vectors can contain color+texture

CSE 803 Fall 2008 Stockman

k means
K-means

CSE 803 Fall 2008 Stockman

histograms can show modes
Histograms can show modes

CSE 803 Fall 2008 Stockman

slide10

Otsu’s method assumes K=2. It searches for the threshold t that optimizes the intra class variance.

CSE 803 Fall 2008 Stockman

url s of other work
URL’s of other work
  • Segmentation lecture http://robots.stanford.edu/cs223b/index.html 
  • Tutorial on graph cut method and assessment of segmentation http://www.cis.upenn.edu/~jshi/GraphTutorial/

CSE 803 Fall 2008 Stockman

segmentation via region growing aggregation

Segmentation via region-growing (aggregation)

Pixels, or patches, at the lowest level are combined when similar in a hierarchical fashion

CSE 803 Fall 2008 Stockman

decision combine neighbors
Decision: combine neighbors?

Neighboring pixel or region

CSE 803 Fall 2008 Stockman

aggregation decision
Aggregation decision

CSE 803 Fall 2008 Stockman

representation of regions
Representation of regions

CSE 803 Fall 2008 Stockman

chain codes for boundaries
Chain codes for boundaries

CSE 803 Fall 2008 Stockman

quad trees divide into quadrants
Quad trees divide into quadrants

M=mixed; E=empty; F=full

CSE 803 Fall 2008 Stockman

can segment 3d images also
Can segment 3D images also
  • Oct trees subdivide into 8 octants
  • Same coding: M, E, F used
  • Software available for doing 3D image processing and differential equations using octree representation.
  • Can achieve large compression factor.

CSE 803 Fall 2008 Stockman

more urls of other work
More URLs of other work
  • Mean shift description http://cmp.felk.cvut.cz/cmp/courses/ZS1/slidy/meanShiftSeg.pdf

CSE 803 Fall 2008 Stockman