DocumentCode
2058337
Title
Feature tree clustering for image segmentation
Author
Inoue, Suguru ; Hagiwara, Masafumi
Author_Institution
Fac. of Sci. & Technol., Keio Univ., Kanagawa, Japan
Volume
3
fYear
2001
fDate
2001
Firstpage
2022
Abstract
A new image segmentation method using a feature tree is proposed in this paper. The feature tree reflects the feature of an image. The proposed method is composed of two processes: (I) learning process and (II) clustering process. In the learning process, many efficient feature trees are made that construct an integrated tree. The integrated tree is used to segment images in the clustering process. Dividing an image is kept on from global point to local point. So, the proposed method can divide images considering not only the local property but also the global property. We applied the proposed method to some images, and obtained good results
Keywords
image segmentation; tree data structures; clustering process; feature tree clustering; global property; image segmentation; integrated tree; learning process; local property; Computer networks; Computer science; Computer vision; Image analysis; Image coding; Image recognition; Image segmentation; Merging; Remote sensing; Tree data structures;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 2001 IEEE International Conference on
Conference_Location
Tucson, AZ
ISSN
1062-922X
Print_ISBN
0-7803-7087-2
Type
conf
DOI
10.1109/ICSMC.2001.973727
Filename
973727
Link To Document