Abstract:

Complex image segmentation is studied to solve the problem of target searching and identification in robot vision. In this context, performance evaluation criteria and emphasis for image segmentation algorithm are proposed explicitly. A modified algorithm is developed based on Mean Shift segmentation method, fully taking into account the effective control of segmentation scale and the scene depth information of the segmentation process. In order to solve the problem of controlling segmentation scale, the concept of edge sensitivity is proposed so that the control ability of the algorithm scale block is improved. Two methods of getting the depth information based on binocular stereo matching and image sensor Kinect are employed to deal with the depth information fusion. Both methods realize the fusion successfully and the performances of segmentation are enhanced obviously. The experiment results demonstrate that the proposed method is more preponderant than traditional algorithms. The proposed algorithm could not only control segmentation scale, but also split the special situations.