IEICE Transactions on Information and Systems

IEICE Transactions on Information and Systems 2007 E90-D(4):791-794; doi:10.1093/ietisy/e90-d.4.791

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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

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

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Manuscript received September 8, 2006.

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This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to My Personal Archive Download to citation manager Request Permissions Google Scholar Articles by EOM, S. Articles by AHN, B. Search for Related Content Social Bookmarking          What's this?