By Topic

A fuzzy-based feature tuning algorithm applied to image segmentation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Chia-Horng Huang ; Dept. of Electr. Eng., Nat. Taiwan Ocean Univ., Keelung, Taiwan ; Yi-Wei Yu ; Jung-Hua Wang

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

Published in:

Systems, Man, and Cybernetics, 2001 IEEE International Conference on  (Volume:4 )

Date of Conference: