A fast object segmentation method for mobile robots based on improved depth information

Due to the rapid development of mobile robots technology, the object recognition is of great practical significance. The real-time performance and robustness of object segmentation in cluttered environments is a considerable problem in robot vision. In this paper, a new object segmentation method using depth information is presented. Firstly, this approach obtains the object candidate region using the depth clue, then accomplished the depth filtering in the object candidate region. Next, the object region is extended to get the better edge information. Finally, the foreground is extracted and the segmentation results is realized on the color image. This method of object segmentation was tested on a real mobile robot platform and the results of experiments confirmed the excellent performance of the proposed method.