• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

An Improved Saliency Detection for Different Light Conditions


Abstract

In this paper, we propose a novel saliency detection framework based on illumination invariant features to improve the accuracy of the saliency detection under the different light conditions. The proposed algorithm is divided into three steps. First, we extract the illuminant invariant features to reduce the effect of the illumination based on the local sensitive histograms. Second, a preliminary saliency map is obtained in the CIE Lab color space. Last, we use the region growing method to fuse the illuminant invariant features and the preliminary saliency map into a new framework. In addition, we integrate the information of spatial distinctness since the saliency objects are usually compact. The experiments on the benchmark dataset show that the proposed saliency detection framework outperforms the state-of-the-art algorithms in terms of different illuminants in the images.


Statistics

Show / Hide Statistics

Statistics (Cumulative Counts from December 1st, 2015)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article

[IEEE Style]
Yongfeng Ren, Jingbo Zhou, Zhijian Wang and Yunyang Yan, "An Improved Saliency Detection for Different Light Conditions," KSII Transactions on Internet and Information Systems, vol. 9, no. 3, pp. 1155-1172, 2015. DOI: 10.3837/tiis.2015.03.018

[ACM Style]
Ren, Y., Zhou, J., Wang, Z., and Yan, Y. 2015. An Improved Saliency Detection for Different Light Conditions. KSII Transactions on Internet and Information Systems, 9, 3, (2015), 1155-1172. DOI: 10.3837/tiis.2015.03.018