DocumentCode :
2037270
Title :
A fuzzy-based feature tuning algorithm applied to image segmentation
Author :
Chia-Horng Huang ; Yi-Wei Yu ; Wang, Junghua
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Ocean Univ., Keelung, Taiwan
Volume :
4
fYear :
2001
fDate :
2001
Firstpage :
2140
Abstract :
Over-segmentation is a serious problem in conventional watershed analysis owing to the topographic relief inherent in the input image. Currently in watershed segmentation methods, merging regions one by one is the most well known cure for the over-segmentation problem, K. Haris et al.(1998) proposed a merging algorithm called fast nearest neighbor region merging based on the observation that it is not necessary to keep all RAG in the heap, only a small portion of them is used to construct nearest neighbor graph (NNG). Although the performance of merging is greatly improved, the required computation time is in proportional to the initial number of regions in NNG. In this paper we propose the fuzzy-based feature tuning (FFT) algorithm that can simultaneously adjust ?i of all region by referencing their adjacent neighboring regions, where ?i is defined as the average gray value over region i
Keywords :
fuzzy logic; image segmentation; merging; average gray value; fast nearest neighbor region merging; fuzzy-based feature tuning algorithm; heap; image segmentation; merging algorithm; nearest neighbor graph; topographic relief; watershed analysis; Clustering algorithms; Filters; Gray-scale; Image analysis; Image segmentation; Merging; Nearest neighbor searches; Performance analysis; Smoothing methods; Surface topography;
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.2001.972872
Filename :
972872
Link To Document :
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