Region Segmentation
Computação Visual e Multimédia
10504: Mestrado em Engenharia Informática
Chap. 7 — Region Segmentation
Chapter 7: Region Segmentation
Outline
Chapter 7: Region Segmentation Image segmentation:���a reminder
Chapter 7: Region Segmentation Image segmentation:���… in pictures
Mea
n S
hift:
A R
obus
t App
roac
h to
war
d Fe
atur
e S
pace
Ana
lysi
s, b
y D
. Com
anic
iu a
nd P
. Mee
r ht
tp://
ww
w.c
aip.
rutg
ers.
edu/
~com
anic
i/MS
PAM
I/msP
amiR
esul
ts.h
tml
Edge segmentation:
Region segmentation:
http
://ro
bots
.sta
nfor
d.ed
u/cs
223b
/inde
x.ht
ml
Chapter 7: Region Segmentation
Chapter 7: Region Segmentation
What is a region?
Chapter 7: Region Segmentation
Region-based approach
Chapter 7: Region Segmentation
Region-based segmentation
€
Ri = Ii=1
n
€
Ri R j =∅ ∀i =1,2,…n
€
P Ri R j( ) = FALSE€
P(Ri) = TRUE, ∀i
Chapter 7: Region Segmentation Comparison of histogram, region growing ���and deformable contour segmentations
3 5 7 3 4 2 1 2 4 9 10 22 9 3 3 5 12 11 15 10 3 5 6 11 9 17 19 1 2 3 11 12 18 16 2 3 6 8 10 18 9 5 4 6 7 8 3 3 1
3 5 7 3 4 2 1 2 4 9 10 22 9 3 3 5 12 11 15 10 3 5 6 11 9 17 19 1 2 3 11 12 18 16 2 3 6 8 10 18 9 5 4 6 7 8 3 3 1
3 5 7 3 4 2 1 2 4 9 10 22 9 3 3 5 12 11 15 10 3 5 6 11 9 17 19 1 2 3 11 12 18 16 2 3 6 8 10 18 9 5 4 6 7 8 3 3 1
3 5 7 3 4 2 1 2 4 9 10 22 9 3 3 5 12 11 15 10 3 5 6 11 9 17 19 1 2 3 11 12 18 16 2 3 6 8 10 18 9 5 4 6 7 8 3 3 1
3 5 7 3 4 2 1 2 4 9 10 22 9 3 3 5 12 11 15 10 3 5 6 11 9 17 19 1 2 3 11 12 18 16 2 3 6 8 10 18 9 5 4 6 7 8 3 3 1
3 5 7 3 4 2 1 2 4 9 10 22 9 3 3 5 12 11 15 10 3 5 6 11 9 17 19 1 2 3 11 12 18 16 2 3 6 8 10 18 9 5 4 6 7 8 3 3 1
3 5 7 3 4 2 1 2 4 9 10 22 9 3 3 5 12 11 15 10 3 5 6 11 9 17 19 1 2 3 11 12 18 16 2 3 6 8 10 18 9 5 4 6 7 8 3 3 1
3 5 7 3 4 2 1 2 4 9 10 22 9 3 3 5 12 11 15 10 3 5 6 11 9 17 19 1 2 3 11 12 18 16 2 3 6 8 10 18 9 5 4 6 7 8 3 3 1
3 5 7 3 4 2 1 2 4 9 10 22 9 3 3 5 12 11 15 10 3 5 6 11 9 17 19 1 2 3 11 12 18 16 2 3 6 8 10 18 9 5 4 6 7 8 3 3 1
3 5 7 3 4 2 1 2 4 9 10 22 9 3 3 5 12 11 15 10 3 5 6 11 9 17 19 1 2 3 11 12 18 16 2 3 6 8 10 18 9 5 4 6 7 8 3 3 1
3 5 7 3 4 2 1 2 4 9 10 22 9 3 3 5 12 11 15 10 3 5 6 11 9 17 19 1 2 3 11 12 18 16 2 3 6 8 10 18 9 5 4 6 7 8 3 3 1
3 5 7 3 4 2 1 2 4 9 10 22 9 3 3 5 12 11 15 10 3 5 6 11 9 17 19 1 2 3 11 12 18 16 2 3 6 8 10 18 9 5 4 6 7 8 3 3 1
threshold T≥10 threshold T≥11 threshold T≥12
region growing with variance of 2 in respect to value 11 with reference to threshold T≥11
deformable contour to meet threshold T≥11
Chapter 7: Region Segmentation
Region growing segmentation
seed growing final region
http
://ue
i.ens
ta.fr
/bai
llie
Chapter 7: Region Segmentation Seed-based region growing segmentation:���pixel aggregation
The seed point can be selected either by a human or automatically by avoiding areas of high contrast (large gradient) => seed-based method.
Chapter 7: Region Segmentation Seed-based region growing ���segmentation: example
original image
threshold: 225~255
threshold: 190~225
threshold = 255 returns multiple seeds
threshold: 155~255
http
://en
.wik
iped
ia.o
rg/w
iki/R
egio
n_gr
owin
g
Problem: To isolate the strongest lightning region of the image on the right hand side without splitting it apart. Solution: To choose the points having the highest gray-scale value which is 255 as the seed points shown in the image immediately below.
Chapter 7: Region Segmentation Fast scanning algorithm:���a kind of unseeded region segmentation
1
Threshold T: P1 == P2 iff Diff(Col(P1),Col(P2)) < T
val=? y
x x==y: val = x x<>y: boundary(x)y if |x-y|≤T new region index if |x-y|>T
1 2 2 3
1 1 1 1 1
If the criterion of homogeneity is local (compared to the value of the candidate pixel and the pixel of the border) => linear method.
http
://ue
i.ens
ta.fr
/bai
llie
Chapter 7: Region Segmentation Region growing segmentation:���advantages & disadvantages
http
://ue
i.ens
ta.fr
/bai
llie
Chapter 7: Region Segmentation
Region splitting and merging segmentation
original image splitting & merging thresholding seg.
Chapter 7: Region Segmentation Region splitting: example���
original image split 1
split 2 split 3
In this example, the criterion of homogeneity is the variance of 1.
http
://ue
i.ens
ta.fr
/bai
llie
Chapter 7: Region Segmentation
Splitting & merging: data structures
RAG with adjacency relations (in red) for big black region.
Chapter 7: Region Segmentation
Splitting & merging segmentation algorithm
RAG with adjacency relations (in red) for big black region.
http
://as
tro.
tem
ple.
edu/
~si
ddu
Chapter 7: Region Segmentation
Watershed segmentation
http
://en
.wik
iped
ia.o
rg/w
iki/W
ater
shed
_(im
age_
proc
essi
ng)#
cite
_not
e-1
watersheds
watershed crest line
Chapter 7: Region Segmentation Watershed segmentation ���by flooding
original image 3D topographic surface
This technique aims at identifying all the third type of points (i.e., points of watershed lines) for segmentation
Chapter 7: Region Segmentation
Watershed segmentation by flooding
http
://eu
clid
.ii.m
etu.
edu.
tr/~
ion5
28/d
emo/
lect
ures
/6/4
/inde
x.ht
ml
255
0
255
0
255
0
255
0
Chapter 7: Region Segmentation
Watershed segmentation algorithm
Chapter 7: Region Segmentation Watershed segmentation algorithm:���dam construction
Chapter 7: Region Segmentation Flooding-based watershed segmentation ���applied to gradient image
original image gradient image
watershed of the gradient image
final contours
http
://cm
m.e
nsm
p.fr
/~be
uche
r/w
tshe
d.ht
ml
Chapter 7: Region Segmentation Marker-controlled watershed ���segmentation (gradient image)
original image over-segmented image
http
://cm
m.e
nsm
p.fr
/~be
uche
r/w
tshe
d.ht
ml
markers of the blobs and of the background
marker-controlled watershed of the gradient image
Chapter 7: Region Segmentation
Inter-pixel watershed segmentation
http
://en
.wik
iped
ia.o
rg/w
iki/W
ater
shed
_(im
age_
proc
essi
ng)#
cite
_not
e-2
Chapter 7: Region Segmentation
More complex segmentation methods
Chapter 7: Region Segmentation
Snakes
Copyright G.D. Hager Images taken from http://www.cs.bris.ac.uk/home/xie/content.htm
Chapter 7: Region Segmentation
Level sets
Copyright G.D. Hager Images taken from http://www.cgl.uwaterloo.ca/~mmwasile/cs870/
Chapter 7: Region Segmentation
Graph cuts
Copyright G.D. Hager Images taken from efficient graph-based segmentation paper
Chapter 7: Region Segmentation Generalized PCA���(Rene Vidal)
Copyright G.D. Hager
Human GPCA
Chapter 7: Region Segmentation
Summary: