基于视觉中心转移的视觉显著性检测方法

针对现有许多检测方法提取出的显著性区域不够清晰的问题,提出一种基于视觉中心偏移的视觉显著性检测方法,在对图像进行预分割的基础上,结合图像的颜色对比特征、颜色分布特征和位置特征,提取出图像显著性区域,利用视觉中心转移模拟人类视野系统的视野转移过程,对图像进行多尺度分析,融合不同尺度显著图得到最终显著图。试验结果表明,本方法较现有显著性检测方法在视觉效果和查准率召回率有明显提高,ROC曲线下的面积可达0.952。

Visual saliency detection based on visual center shift

Many existing detection methods could not extract saliency regions clearly. A novel saliency detection method based on visual center offsetting was proposed. On the basis of images' pre-segmentation, combining with color contrast features, color distribution features and location features, saliency region of an image was extracted. The center offsetting was used to simulate the vision transfer process of human, after multi-scale analysis, by fusing saliency maps at different scales. The final saliency map was computed. The results showed that the performance of the proposed method was better on visual effect and the precision recall rate than existing methods, the area under ROC curve was 0.952.