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视觉模型标定中的高精度图像特征提取算法

High Accuracy Detection of Image Features in Vision Model Calibration

  • 摘要: 针对平面网状标定样板建立了一种获取图像特征的高精度提取算法经过亚像素边缘提取和边缘跟踪等步骤,区分开样板图像中的十字线与小方块,确定十字线的中心线与小方块的中心点,获得精确的图像特征对噪声仿真图像和真实图像进行处理,并给出了实验结果.

     

    Abstract: In computer stereovision, the extraction of 3D space information and shape reconstruction from 2D stereo images depend largely on the vision model. Calibration of the vision model parameters has been and continues to be, one of the most heavily investigated topics in computer stereovision. Aiming at plane calibration sample with grids, a high accuracy method for detecting image features is presented. By using sub-pixel edge detection and edge tracking etc, small square edges and cross edges of the calibration sample image are distinguished, then center lines of the cross and focuses of the small squares are determined, and accurate image features are detected. The method presented is applied to images with simulated noise and real images. The experiment results are given at the end of this paper.

     

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