A Framework for Segmentation Using Edge Guided Image Clustering
Keywords:
Image segmentation, fuzzy k-means clustering, canny edge.Abstract
—Region segmentation and edge detection are
standard image processing operations. Clustering can be used for region segmentation. However, often clustering results depend on the selection of various parameters, such as the number of clusters, or the clustering algorithm used. The framework presented here employs the result of edge detection on the original image, as well as on the clustering results of the same image, to automatically select (according to some
agreement measure) the optimal number of clusters, and the corresponding (best) segmentation. The framework supports an extended pixel representation in which other information, such as texture, can be incorporated in addition to edge and region information. To illustrate this framework, the edge
guided clustering algorithm presented here, uses the Canny edge detection approach to guide region identification through fuzzy k-means clustering. Experimental results on benchmark images for which manual segmentation is available as reference illustrate the effectiveness of this approach.
Downloads
Downloads
Published
Issue
Section
License
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
