Salient region detection for complex background images using integrated features

We develop a novel algorithm for detecting salient regions. By analyzing the advantages and disadvantages of existing methods, five principles for designing salient region detection algorithms are summarized. Based on these principles, we propose a novel method that generates saliency map with highlighted salient regions by utilizing two different features, namely visual saliency value and spatial weight. The visual saliency value is determined based on local contrast differences and low-level feature frequencies. The spatial weight is computed by analyzing the size and locations of salient regions. Extensive experiments on benchmark image dataset demonstrate that the proposed algorithm outperforms seven state-of-the-art methods on complex background images.