Study on the Image Segmentation Algorithm with Depth Data of Kinect

Abstract:

In the segmentation algorithms of the depth image, because the object and its support surface are continuous in the depth data ,the traditional method of edge detection methods can’t detect the edge between the object and its support surface. To solve this problem, the segmentation algorithm of the depth image is studied in this paper. Firstly, we use canny operator to detect the edge the of depth image of the scene. Then the depth image of the scene is transformed into points of a 3-D space coordinate and normal vector is calculated for each point. The method of calculation the direction of the normal vector is used to determine the point of which belongs to the support surface area, which determine the support surface area of the scene. Finally, we detect image edge of the image that the support surface area is extracted, and fuse the result of canny operator edge detection and edge of the image that the support surface area is extracted. Experiments show that the segmentation algorithm works well, which the problem of detection the edge between the support surface area and the object and can also achieve a good depth image segmentation.

• Periodical: Advanced Materials Research (Volumes 998-999)
• Pages: 929-933
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.998-999.929
• Online since: July 2014
• Authors: Lu Yi Li*, Jun Yong Ye
• Keywords: 3D, Canny, Depth Image, Edge Detection, Segmentation

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