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 :
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