XLA-LQN-TUAN 9.pdf
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Transcript of XLA-LQN-TUAN 9.pdf
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X l nh s v video s nng caoTun9: Phn onnh
TS. L QucNgc
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Ni dung
10.1. Pht biubi ton10.2. Region growing
10.3. K-means
10.4. HAC (Hierarchical Agglomerative Clustering)
2TS. L Quc Ngc
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10.1. Pht biu bi ton
Giscnphn onnh thnh N vngCnxc nhlutphn on sao cho
3TS. L Quc Ngc
NRRR ,...,, 21I
)(RP
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1
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10.2. Region growing
Nguyn lGeometrical proximity + homogeneity -> connected
image regions.
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10.2. Region growing
Phngphp- Khinguntmtsimmm, lan tankhi phton bnh.
-hinthcviclan tacnxc nh.immm
. Lutlan tavvtr
. Lutkimtra tnh thunnhtcavng sau mibclan ta.
5TS. L Quc Ngc
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10.2. Region growing
Phngphp. Lutlan tavvtr
Lan tatheo ln cn8.
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10.2. Region growing
Phngphp. Lutkim tra tnh thunnhtcavng sau mibclan ta.
Tibcthk, vimivng
Kimtra cc pixels chacphn lptrong ln cn
8 camipixel thucbin cavng.
Nu th ktnp
pixel vo vng
8TS. L Quc Ngc
NiR ki ,...,2,1,)(
TrueyxbRP kiki )}),({( )()( ),()( yxb ki
)(kiR
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10.2. Region growing
Phngphp
. Lutkim tra tnh thunnhtcavng sau mibclan ta.
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)()()(
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ki
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10.2. Region growing
Phngphp
. Lutmerge vng.
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)(|)()(|
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10.3. K-means
Nguyn lhomogeneity -> image regions.
12TS. L Quc Ngc
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Bahadir K. Gunturk EE 7730 - Image Analysis I 13
10.3. K-means
1. Partition the data points into K clusters randomly. Find thecentroids of each cluster.
2. For each data point:
Calculate the distance from the data point to each cluster.
Assign the data point to the closest cluster.
3. Recompute the centroid of each cluster.
4. Repeat steps 2 and 3 until there is no further change in the
assignment of data points (or in the centroids).
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10.3. K-means
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10.3. K-means
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10.3. K-means
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10.3. K-means
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10.3. K-means
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Bahadir K. Gunturk EE 7730 - Image Analysis I 19
10.3. K-means
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Bahadir K. Gunturk EE 7730 - Image Analysis I 20
10.3. K-means
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10.3. K-means
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10.3. K-means
RGB vector
xj
i
2
jelements of i'th cluster
iclusters
K-means clustering minimizes
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Bahadir
K.Gunturk
EE 7730 - Image Analysis I 23
10.3. K-means
Example
Original K=5 K=11
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10.3. K-means
Phngphp
24TS. L Quc Ngc
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10.4. HAC
Nguyn l
homogeneity -> image regions.
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10.4. HAC
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10.4. HAC
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10.4. HAC
Phng
php
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10.4. HACPhngphp
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10.4. HACPhngphp
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10.4. HACPhngphp
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