DocumentCode :
3003298
Title :
Two-Dimensional Arimoto Entropy Image Thresholding based on Ellipsoid Region Search Strategy
Author :
Liu, Yaoyong ; Li, Shuguang
Author_Institution :
Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China
fYear :
2010
fDate :
29-31 Oct. 2010
Firstpage :
1
Lastpage :
4
Abstract :
In this paper, a novel image thresholding based on Two-Dimensional Arimoto Entropy (TDAE), called Ellipsoid Region Search Strategy (ERSS), is proposed. The basic idea is to search the optimal threshold from the reference point obtained by one-dimensional OTSU algorithm. Different from existing approaches, our approach provides a scheme to reduce the number of samples through the existing relatively easy and efficient algorithm. Additionally, this approach improves the performance of image segmentation. The experimental results on image segmentation demonstrate that our method is not only significantly more efficient but also accelerates the computation speed of two-dimensional Arimoto entropic thresholding algorithms.
Keywords :
entropy; image segmentation; query formulation; ellipsoid region search strategy; image segmentation; one dimensional OTSU algorithm; optimal threshold; reference point; two dimensional Arimoto entropy image thresholding; Algorithm design and analysis; Artificial neural networks; Entropy; Histograms; Image segmentation; Pattern recognition; Pixel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Technology (ICMT), 2010 International Conference on
Conference_Location :
Ningbo
Print_ISBN :
978-1-4244-7871-2
Type :
conf
DOI :
10.1109/ICMULT.2010.5631047
Filename :
5631047
Link To Document :
بازگشت