NDLI: A fuzzy-based feature tuning algorithm applied to image segmentation

Content Provider	IEEE Xplore Digital Library
Author	Chia-Horng Huang Yi-Wei Yu Jung-Hua Wang
Copyright Year	2000
Description	Author affiliation: Dept. of Electr. Eng., Nat. Taiwan Ocean Univ., Keelung, Taiwan (Chia-Horng Huang)
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 ?/sub i/ of all region by referencing their adjacent neighboring regions, where ?/sub i/ is defined as the average gray value over region i.
Sponsorship	Raytheon
Starting Page	2140
Ending Page	2144
File Size	424034
Page Count	5
File Format	PDF
ISBN	0780370872
ISSN	1062922X
DOI	10.1109/ICSMC.2001.972872
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-10-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Merging Surface topography Filters Image analysis Gray-scale Clustering algorithms Nearest neighbor searches Performance analysis Smoothing methods
Content Type	Text
Resource Type	Article

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