NDLI: Image segmentation based on fuzzy flood fill mean shift algorihm

Content Provider	IEEE Xplore Digital Library
Author	Hoon Kang Seung Hwan Lee Jayong Lee
Copyright Year	2010
Description	Author affiliation: The School of Electrical and Electronics Engineering, Chung-Ang University, Seoul 156-756, Korea (Hoon Kang; Seung Hwan Lee; Jayong Lee)
Abstract	In this paper, the fuzzy flood fill mean shift algorithm is introduced. This algorithm is developed for the methodology of robust segmentation by improving the mean shift algorithm through the fuzzy kernels and the flood fill technique, instead of those based on the spatial bandwidth. Due to this exchange, the flood fill mean shift involves only one parameter, the range bandwidth, which is less sensitive and is able to acquire the global characteristics. If the image parts affected by the illumination changes are sufficiently small and their boundaries are not clear, the illumination effects do not have an influence on the mode seeking procedure of the proposed fuzzy flood fill mean shift. To prove the usefulness and the validity of our algorithm, we present several experiments and analysis of the results.
Starting Page	1
Ending Page	6
File Size	726588
Page Count	6
File Format	PDF
ISBN	9781424478590
e-ISBN	9781424478583
e-ISBN	9781424478576
DOI	10.1109/NAFIPS.2010.5548413
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-12
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Floods Lighting Kernel Robustness Clustering algorithms Iterative algorithms Bandwidth Computer vision Algorithm design and analysis Robot Vision component Mean Shift Segmentation Kernel Density Estimation Floodfill
Content Type	Text
Resource Type	Article

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