DocumentCode :
2894540
Title :
On Improving Image Segmentation
Author :
Khan, Asmar A. ; Xydeas, Costas ; Ahmed, Hassan
Author_Institution :
Sch. of Comput. & Commun., Lancaster Univ., Lancaster, UK
fYear :
2011
fDate :
Nov. 28 2011-Dec. 1 2011
Firstpage :
213
Lastpage :
217
Abstract :
The proposed scheme is an approach which can be used to improve the performance of traditional image segmentation systems. The scheme is based on a framework that employs the output of an existing image segmentation process together with hierarchical clustering using an information theoretic similarity measure. Experimental results clearly show that when the scheme operates in conjunction with a state of the art image segmentation algorithm, it yields significantly superior performance over a wide spectrum of natural images. These results are based on informal subjective evaluation tests as well as on objective measurements obtained from processing the Berkeley BSDS 300 image dataset.
Keywords :
image segmentation; natural scenes; pattern clustering; visual databases; Berkeley BSDS 300 image dataset; hierarchical clustering; image processing; image segmentation algorithm; information theoretic similarity measures; natural images; Computer vision; Image edge detection; Image segmentation; Pattern recognition; Q measurement; System performance; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal-Image Technology and Internet-Based Systems (SITIS), 2011 Seventh International Conference on
Conference_Location :
Dijon
Print_ISBN :
978-1-4673-0431-3
Type :
conf
DOI :
10.1109/SITIS.2011.48
Filename :
6120652
Link To Document :
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