A Salient Region Detection Method Based on Frequency-Tuning and One-Cut Algorithm

Domestic robots have shown up in more and more families in recent years. When they follow the order from the host and serve a family, it is involved in many techniques such as object recognition, object grasping and so on. So target segmentation is a particularly important technology, which is also a very challenging problem in the field of image analysis and computer vision. Based on the previous work, we can see that the Frequency- Tuned salient region detection (FT) is superior in performance and computational efficiency and can meet the realtime requirements of the robot system. However, the output result is a saliency map in pixels at full resolution, which contains no “object“ concept. In order to extract the complete salient region, we fuse FT algorithm and One-Cut segmentation method to achieve automatic segmentation of salient goals. In addition, the accuracy and robustness of saliency region segmentation are improved by using connected component attributes and depth gradient features.