DocumentCode :
3599426
Title :
The Hybrid Approach of Image Segmentation Using MeanShift and Saliency Maps
Author :
Ta, Tuan A. ; Cao, Tru H. ; Nguyen, Tiep V.
Author_Institution :
John von Neumann Inst. - VNUHCM, Ho Chi Minh City, Vietnam
fYear :
2012
Firstpage :
11
Lastpage :
17
Abstract :
Image segmentation is an important problems in the field of image processing. In this paper, we propose a hybrid approach of image segmentation, combining MeanShift, an image segmentation method, and Saliency Maps, a regions-of-interest detection method. Our proposed method uses low-level features of color image, such as luminance, color and spatial. The results from experiments showed that our proposed method solves two problems, one is determining the regions of objects with high saliency in image and the other is associating discrete broken regions based on the relationship between low-level features and saliency feature.
Keywords :
feature extraction; image colour analysis; image segmentation; discrete broken regions; high image saliency; image processing; image segmentation; low-level color image feature; mean shift; regions-of-interest detection method; saliency maps; Biological system modeling; Cities and towns; Computational modeling; Feature extraction; Image color analysis; Image segmentation; Visualization; Feature-based Segmentation; Image Segmentation; Low-level Features; Salient Regions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Knowledge and Systems Engineering (KSE), 2012 Fourth International Conference on
Print_ISBN :
978-1-4673-2171-6
Type :
conf
DOI :
10.1109/KSE.2012.20
Filename :
6299392
Link To Document :
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