During the process of three-dimensional vision inspection for products, the target objects under the complex background
are usually immovable. So the desired three-dimensional reconstruction results can not be able to be obtained because of
achieving the targets, which is difficult to be extracted from the images under the complicated and diverse background.
Aiming at the problem, a method of three-dimensional reconstruction based on the graph theoretic segmentation and
multiple views is proposed in this paper. Firstly, the target objects are segmented from obtained multi-view images by
the method based on graph theoretic segmentation and the parameters of all cameras arranged in a linear way are gained
by the method of Zhengyou Zhang calibration. Then, combined with Harris corner detection and Difference of Gaussian
detection algorithm, the feature points of the images are detected. At last, after matching feature points by the triangle
method, the surface of the object is reconstructed by the method of Poisson surface reconstruction. The reconstruction
experimental results show that the proposed algorithm segments the target objects in the complex scene accurately and
steadily. What’s more, the algorithm based on the graph theoretic segmentation solves the problem of object extraction
in the complex scene, and the static object surface is reconstructed precisely. The proposed algorithm also provides the
crucial technology for the three-dimensional vision inspection and other practical applications.