DocumentCode :
590655
Title :
Gradient-based global features and its application to image retargeting
Author :
Ito, Izumi
Author_Institution :
Tokyo Inst. of Technol., Tokyo, Japan
fYear :
2012
fDate :
3-6 Dec. 2012
Firstpage :
1
Lastpage :
4
Abstract :
We propose gradient-based global features and its application to image retargeting. The proposed features are used for an importance map for image retargeting, which represents rough location of salient objects in an image. We focus on areas rather than points and lines to be assigned as an important part. The information about areas in multiple layers provides global features. Experimental results compared to the state-of-the-art salient features for image retargeting demonstrate the effectiveness of the proposed features.
Keywords :
feature extraction; gradient methods; image colour analysis; gradient-based global features; image retargeting; rough location; salient object; Computer vision; Histograms; Image color analysis; Image edge detection; Image segmentation; Niobium; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal & Information Processing Association Annual Summit and Conference (APSIPA ASC), 2012 Asia-Pacific
Conference_Location :
Hollywood, CA
Print_ISBN :
978-1-4673-4863-8
Type :
conf
Filename :
6411802
Link To Document :
بازگشت