Title :
A visual saliency detection algorithm based on channel selecting in transform domains
Author :
Shen Yifeng ; Niu Yifeng ; Shen Lincheng
Author_Institution :
Coll. of Mechatron. Eng. & Autom., Nat. Univ. of Defense Technol., Changsha, China
fDate :
May 31 2014-June 2 2014
Abstract :
A transform domain algorithm using channel selecting is proposed for visual saliency in this paper. This algorithm is able to improve the accuracy of the traditional transform domain saliency detection while preserving their advantage of fast processing speed. Based on the image signature algorithm, we select the channels by calculating the correlation values between each channel. Then, the selected channels, instead of all of the channels, are combined for the final saliency map according to the corresponding combination rule which we designed. The experimental comparison between the proposed and original approaches demonstrates that our method is higher in accuracy while maintaining high processing speed.
Keywords :
object detection; transforms; channel selection; combination rule; correlation values; image signature algorithm; saliency map; transform domain algorithm; visual saliency detection algorithm; Accuracy; Algorithm design and analysis; Correlation; Detection algorithms; Fourier transforms; Visualization; Channel Selecting; Image Signature; Saliency Detection; Transform Domain;
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
DOI :
10.1109/CCDC.2014.6852634