结合目标色彩特征的基于注意力的图像分割

Attention-based image segmentation method by combining target colors

提出一种基于注意力的图像分割算法,在视觉场景选择机制基础上结合目标色彩特征的任务驱动机制,形成了自下而上和自上而下的注意力集成分割机理。该算法在图像的多尺度空间中,把视觉场景的亮度、颜色和方向特征与任务目标色彩特征同时进行提取,生成场景和目标相结合的显著图,然后在基于视觉注意力图像空间中对"场景-目标"显著图进行归一化的跨尺度融合,最后通过双线性插值和显著图连通区域二值化分割出图像目标注意力焦点。应用该算法对自然场景与室内场景图像进行实验,结果表明该方法在各种环境中尤其是干扰物体较显著的情形下都能成功地分割提取出目标物体。

An attention-based approach for image segmentation is proposed. It integrates the bottom-up and top-down attention mechanism, to form a scene-target selection method for the target objects in an image. In the multi-scale space of image, this algorithm simultaneously extracts the intensity, color and orientation features of the scene image and the color feature of the target object to generate the scene-target saliency map. Then, it processes the saliency map by combination the multi-scale scene-target images with normalization of the image features. Finally, the target object is obtained by double-interpolation and black-white segmentation of the scene image. By applying the algorithm to the images in natural scene and indoor environment, experiment is conducted. The experimental results indicate that the algorithm can successfully segment the scene image and extract the target object in any condition, and exhibit good robustness even for the scene image with noisy objects.