DocumentCode :
626687
Title :
A novel region merging based image segmentation approach for automatic object extraction
Author :
Lin Zha ; Zhi Liu ; Shuhua Luo ; Liquan Shen
Author_Institution :
Sch. of Commun. & Inf. Eng., Shanghai Univ., Shanghai, China
fYear :
2013
fDate :
19-23 May 2013
Firstpage :
970
Lastpage :
973
Abstract :
This paper presents a novel region merging based automatic image segmentation approach, which is applicable for object extraction. From an initial over-segmentation result, we exploit the regional histogram based similarity measure as merging criterion and merging order determination scheme with three priorities, to efficiently perform region merging, which is recorded using a binary partition tree (BPT). Based on the analysis of BPT, an appropriate subset of BPT nodes is selected to represent a meaningful image segmentation result and object extraction result. Experimental results demonstrate the better segmentation performance of our approach.
Keywords :
feature extraction; image segmentation; trees (mathematics); BPT nodes; automatic object extraction; binary partition tree; order determination scheme; region merging based image segmentation approach; regional histogram; Algorithm design and analysis; Histograms; Image color analysis; Image segmentation; Indexes; Merging; Partitioning algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems (ISCAS), 2013 IEEE International Symposium on
Conference_Location :
Beijing
ISSN :
0271-4302
Print_ISBN :
978-1-4673-5760-9
Type :
conf
DOI :
10.1109/ISCAS.2013.6572010
Filename :
6572010
Link To Document :
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