DocumentCode :
1835940
Title :
Fusion based object detection
Author :
Suja, T. Baby ; John, Mala
Author_Institution :
Dept. of Electron. Eng., Anna Univ., Chennai, India
fYear :
2010
fDate :
29-31 Jan. 2010
Firstpage :
1
Lastpage :
3
Abstract :
Fusion based object detection method presented herein combines local and global features for object detection. The cluster based part detection facilitates adequate representation for the individual local parts of an image that carry the significant features of the object. The chain code is used for deriving the local and global information. The genetic algorithm is used to combine all the local and global features. The algorithm is tested on a set of real-world images which contain side views of cars and found to yield very good results with no false alarm within the data base that was used for testing.
Keywords :
image fusion; image representation; object detection; pattern clustering; chain code; cluster based part detection; fusion based object detection; image representation; Clustering algorithms; Computer vision; Detection algorithms; Detectors; Genetic algorithms; Image edge detection; Image segmentation; Object detection; Pediatrics; Testing; Genetic algorithm and multi-classifier fusion; Multimedia retrieval; Object detection; chain code;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications (NCC), 2010 National Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4244-6383-1
Type :
conf
DOI :
10.1109/NCC.2010.5430203
Filename :
5430203
Link To Document :
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