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A Novel Camera Parameters Auto-adjusting Method Based on Image Entropy

机译:一种基于图像熵的新型摄像机参数自动调整方法

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How to make vision system work robustly under dynamic light conditions is still a challenging research focus in robot vision community. In this paper, a novel camera parameters auto-adjusting method based on image entropy is proposed. Firstly image entropy is defined and its relationship with camera parameters is verified by experiments. Then how to optimize the camera parameters based on image entropy is proposed to make robot vision adaptive to the different light conditions. The algorithm is tested using the omnidirectional vision system in indoor RoboCup Middle Size League environment and outdoor RoboCup-like environment, and the results show that our method is effective and color constancy to some extent can be achieved.
机译:如何在动态光线条件下稳健地制定视觉系统,仍然是机器人视觉社区的具有挑战性的研究。本文提出了一种基于图像熵的新型摄像机参数自动调整方法。首先定义图像熵,并通过实验验证其与相机参数的关系。然后,提出了如何优化基于图像熵的相机参数,以使机器人视觉适应不同的光线。该算法使用室内红舱中型联赛环境和室外Robocup的环境中的全向视觉系统进行测试,结果表明,我们的方法在一定程度上是有效的并且颜色恒定。

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