For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
Cellular Watersheds: A Parallel Implementation of the Watershed Transform on the CNN Universal Machine
Seongeun EOM Vladimir SHIN Byungha AHN
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2007/04/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Processing and Video Processing
watershed transform, parallel implementation, cellular neural network universal machine, image segmentation,
Full Text: PDF>>
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.