Near-infrared monocular vision measurement and reference image self-healing of object random rough surface
In response to the special situation where the near-infrared monocular vision pose measurement system in complex application environments deviates from the preset cooperative target object and cannot complete pose measure-ment,a monocular vision measurement method based on the random rough surface image around the cooperative target is proposed,as well as a dynamic self-healing method after image damage.By matching and calculating the real-time acquired features of the random rough surface image with the pre stored reference image features,emergency measure-ment in special situations is completed.At the same time,in order to reduce the impact on the pose measurement accura-cy after the pollution or damage of the random rough surface image,real-time computing calculation of the degree of pollution or damage and dynamic self-healing of the reference image features.The experimental results show that the pose measurement accuracy of the random rough surface object is slightly lower than that of the cooperative target ob-ject,but it can meet the emergency use needs in special situations and improve the robustness of the measurement sys-tem.When the pollution or damage of the random rough surface image reaches 70%,using self-healing processing re-duces the azimuth measurement error by more than 72%compared to not doing self-healing processing,verifying the ef-fectiveness of the benchmark image self-healing method.
the object follows the rough surfacenear-infrared monocular vision measurementreference image self-healingreference image featuresfeature matching
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