DocumentCode :
483292
Title :
An Efficient Hierarchical Method for Image Shadow Detection
Author :
Rao Bin ; Zheng Gang ; Chen Tiemin ; Huang Jian ; Shao Xi
Author_Institution :
Flight Simulator Training Center, Civil Aviation Flight Univ. of China, Guanghan
fYear :
2009
fDate :
23-25 Jan. 2009
Firstpage :
622
Lastpage :
627
Abstract :
Shadow image edge detection by using an adaptive background model is a critical component for many vision-based applications. Most background models were maintained in pixel-based forms, while some approaches began to study block-based representations which are more robust to non-stationary backgrounds. In this paper, a novel method that combines edge growing and granular computing approaches into a single framework is proposed. Efficient hierarchies can be built with these two approaches complementary to each other. In addition, a novel model is proposed for shadow edge using edge growing from the edge nodes in the coarse level of the hierarchy. As can be seen from the experimental analysis, the method we proposed has better performance than existing single-level approaches in edge detection and image segmentation.
Keywords :
computer vision; edge detection; image representation; image segmentation; adaptive background model; block-based representations; edge growing; granular computing; image segmentation; image shadow detection; pixel-based forms; shadow edge; shadow image edge detection; vision-based applications; Aerospace engineering; Aerospace simulation; Data mining; Educational institutions; Geometry; Image edge detection; Image segmentation; Information technology; Light sources; Mobile communication; edge growing; grauluar computing; shadow detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Knowledge Discovery and Data Mining, 2009. WKDD 2009. Second International Workshop on
Conference_Location :
Moscow
Print_ISBN :
978-0-7695-3543-2
Type :
conf
DOI :
10.1109/WKDD.2009.112
Filename :
4772014
Link To Document :
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