Abstract: Abstract: In recent years, the instance segmentation technology has received more attention. Although the Mask R-CNN instance segmentation method is important in the field of instance segmentation, the resultant edge of each instance cannot entirely match the real edge. In order to solve this problem, a method was proposed that combined the result of the salient object extraction with that of the mask R-CNN instance segmentation, so as to produce a better edge of instance segmentation. First, the image was recognized by Mask R-CNN, with the segmentation result obtained. Then PoolNet was utilized to process the detected image, resulting in the salient object information in the image. At last, the edge of the mask image was optimized by the result of PoolNet, attaining a better result of the edge segmentation. After testing, this method can yield better segmentation results than Mask R-CNN for most of images with salient targets in some important indexes.

Key words: Keywords: instance segmentation, Mask R-CNN, salient object, edge optimization, mask information