CAJ | 학술논문

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。
제출일충기우주의력적도상분할산법，재시각장경선택궤제기출상결합목표색채특정적임무구동궤제，형성료자하이상화자상이하적주의력집성분할궤리。해산법재도상적다척도공간중，파시각장경적량도、안색화방향특정여임무목표색채특정동시진행제취，생성장경화목표상결합적현저도，연후재기우시각주의력도상공간중대“장경-목표”현저도진행귀일화적과척도융합，최후통과쌍선성삽치화현저도련통구역이치화분할출도상목표주의력초점。응용해산법대자연장경여실내장경도상진행실험，결과표명해방법재각충배경중우기시간우물체교현저적정형하도능성공지분할제취출목표물체。
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.