DocumentCode :
3516346
Title :
Robust Segmentation Using Marked Regular Pyramid and Mean Shift
Author :
Li An ; Xu Xue-mei ; Guo Qiaoyun ; Mo Qin
Author_Institution :
Inst. of Phys., Central South Univ., Changsha, China
fYear :
2010
fDate :
28-29 Oct. 2010
Firstpage :
341
Lastpage :
344
Abstract :
This paper describes a novel fast mean shift algorithm based on a resampling technique with marked regular pyramid structure. This new method focuses on solving the problem of high calculation complexity when high data dimension or large data sets are involved in mean shift. By resampling the original image with marked regular pyramid structure, improved method reduces the number of pixels requiring mean-shift iterations and also reduces the complexity of the mean shift algorithm. The proposed approach is efficient in providing good segmentation performance. The experimental results demonstrate the effectiveness of the proposed approach.
Keywords :
image resolution; image sampling; image segmentation; fast mean shift algorithm; large data sets; marked regular pyramid; mean-shift iterations; pixels; resampling technique; robust segmentation; Algorithm design and analysis; Artificial neural networks; Complexity theory; Image color analysis; Image segmentation; Kernel; Pixel; hierarchy; image segmentation; marked regular pyramid; mean shift;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligence Information Processing and Trusted Computing (IPTC), 2010 International Symposium on
Conference_Location :
Huanggang
Print_ISBN :
978-1-4244-8148-4
Electronic_ISBN :
978-0-7695-4196-9
Type :
conf
DOI :
10.1109/IPTC.2010.53
Filename :
5663238
Link To Document :
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