## Image clustering using fuzzy graph theory

We propose an image clustering algorithm which uses fuzzy graph theory. First, we define a fuzzy graph and the concept of connectivity for a fuzzy graph. Then, based on our definition of connectivity we propose an algorithm which finds connected subgraphs of the original fuzzy graph. Each connected subgraph can be considered as a cluster. As an application of our algorithm, we consider a database of images. We calculate a similarity measure between any pairs of images in the database and generate the corresponding fuzzy graph. Then, we find the subgraphs of the resulting fuzzy graph using our algorithm. Each subgraph corresponds to a cluster. We apply our image clustering algorithm to the key frames of news programs to find the anchorperson clusters. Simulation results show that our algorithm is successful to find most of anchorperson frames from the database.

### Duke Scholars

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## Publication Date

## Volume

## Start / End Page

## Related Subject Headings

- 5102 Atomic, molecular and optical physics
- 4009 Electronics, sensors and digital hardware
- 4006 Communications engineering

### Citation

*Proceedings of SPIE - The International Society for Optical Engineering*(Vol. 3972, pp. 245–252).

*Proceedings of SPIE - The International Society for Optical Engineering*, 3972:245–52, 2000.

*Proceedings of SPIE - The International Society for Optical Engineering*, vol. 3972, 2000, pp. 245–52.

## Published In

## ISSN

## Publication Date

## Volume

## Start / End Page

## Related Subject Headings

- 5102 Atomic, molecular and optical physics
- 4009 Electronics, sensors and digital hardware
- 4006 Communications engineering