Skip Navigation

IEICE Transactions on Information and Systems 2007 E90-D(4):791-794; doi:10.1093/ietisy/e90-d.4.791
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Request Permissions
Google Scholar
Right arrow Articles by EOM, S.
Right arrow Articles by AHN, B.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Copyright © 2007 The Institute of Electronics, Information and Communication Engineers

Regular Section -- Letters -- Image Processing and Video Processing

Cellular Watersheds: A Parallel Implementation of the Watershed Transform on the CNN Universal Machine

Seongeun EOM1, Vladimir SHIN1 and Byungha AHN1

1 The authors are with the Department of Mechatronics, Gwangju Institute of Science and Technology (GIST), 1 Oryoung-dong, Buk-gu, Gwangju, South Korea. E-mail: seueom{at}gist.ac.kr


  Abstract

The watershed transform has been used as a powerful morphological segmentation tool in a variety of image processing applications. This is because it gives a good segmentation result if a topographical relief and markers are suitably chosen for different type of images. This paper proposes a parallel implementation of the watershed transform on the cellular neural network (CNN) universal machine, called cellular watersheds. Owing to its fine grain architecture, the watershed transform can be parallelized using local information. Our parallel implementation is based on a simulated immersion process. To evaluate our implementation, we have experimented on the CNN universal chip, ACE16k, for synthetic and real images.

Key Words: watershed transform, parallel implementation, cellular neural network universal machine, image segmentation

Manuscript received September 8, 2006.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.