Techniques for CBIR

03/10/1603/10/16

陳慶鋒陳慶鋒

Outline

Iteration-free clustering algorithm for Iteration-free clustering algorithm for nonstationary image databasenonstationary image database

Simulation resultSimulation result Possible research domainPossible research domain ReferencesReferences

Iteration-free clustering

Nonstationary image databaseNonstationary image database

feature-based indexing methodfeature-based indexing method

ex:histogram,ccv…ex:histogram,ccv…

indexing structuresindexing structures

ex:binary tree, R-tree….ex:binary tree, R-tree….

images may be added or deleted from images may be added or deleted from

the database the database

Iteration-free clustering (cont.)

K-mean clusteringK-mean clustering

optimal clustering, but time consumingoptimal clustering, but time consuming Iteration-free clusteringIteration-free clustering

sub-optimal clustering, but more efficientsub-optimal clustering, but more efficient

Iteration-free clustering (cont.)

AlgorithmAlgorithm

a. Generating separating hyperplanea. Generating separating hyperplane

b. Updating separating hyperplanes using b. Updating separating hyperplanes using

IFC algorithm IFC algorithm

Iteration-free clustering (cont.)

Generating separating hyperplane:Generating separating hyperplane:

initial hyperplane: initial hyperplane:

generated by k-mean algorithmgenerated by k-mean algorithm

Iteration-free clustering (cont.) 2-D feature space2-D feature space

Iteration-free clustering (cont.)

Iteration-free clustering (cont.)

Iteration-free clustering (cont.)

Iteration-free clustering (cont.)

AlgorithmAlgorithm

a. Generating separating hyperplanea. Generating separating hyperplane

b. Updating separating hyperplanes using b. Updating separating hyperplanes using

IFC algorithmIFC algorithm

Iteration-free clustering (cont.)

Updating separating hyperplanes using IFC Updating separating hyperplanes using IFC algorithmalgorithm

1) Translation of hyperplanes1) Translation of hyperplanes

2) Rotation of hyperplanes2) Rotation of hyperplanes

Iteration-free clustering (cont.)

Translation of hyperplanesTranslation of hyperplanes

first partitions the new-coming feature vectors according first partitions the new-coming feature vectors according to original hyperplaneto original hyperplane

Iteration-free clustering (cont.)

Translation of hyperplanes(cont.)Translation of hyperplanes(cont.)

The database’s midvector becomes The database’s midvector becomes m’m’ instead of instead of

m.m.

Iteration-free clustering (cont.) The suboptimal midvector The suboptimal midvector m’m’ outperforms the outperforms the

midvector of KMIOmidvector of KMIO

Iteration-free clustering (cont.)

Rotation of hyperplanesRotation of hyperplanes

To obtain the rotation of the new hyperplane To obtain the rotation of the new hyperplane H’H’, the best , the best representative line segment must be found first.representative line segment must be found first.

Distance of Distance of xx and : and :

Iteration-free clustering (cont.)

Rotation of hyperplanes(cont.)Rotation of hyperplanes(cont.) is estimated according to the four vectors is estimated according to the four vectors

,rather than by reapplying K-mean algorithm to determine ,rather than by reapplying K-mean algorithm to determine new representative feature vectors.new representative feature vectors.

the cost function the cost function FF::

Iteration-free clustering (cont.)

Rotation of hyperplanes(cont.)Rotation of hyperplanes(cont.) The best representative line segment must have minimum The best representative line segment must have minimum

cost and pass through the new midvector cost and pass through the new midvector m’m’..

Thus, the Lagragian function Thus, the Lagragian function LL is: is:

Iteration-free clustering (cont.)

Simulation result

Possible Research Domain

New feature vectors for CBIRNew feature vectors for CBIR New indexing structure for image databaseNew indexing structure for image database

References

[2]Chia H. Yeh, Chung J. Kuo, “Iteration-free [2]Chia H. Yeh, Chung J. Kuo, “Iteration-free clustering algorithm for nonstationary image clustering algorithm for nonstationary image database,” Multimedia, IEEE Transaction on, database,” Multimedia, IEEE Transaction on, vol. 5, no. 2, JUNE 2003, pp. 223-236vol. 5, no. 2, JUNE 2003, pp. 223-236