With the continuous development of computer science and technology, symbol recognition systems may be converted from two-dimensional space to three-dimensional space. Therefore, this article mainly introduces the symbol recognition system based on 3D stereo vision. The three-dimensional image is taken by the visual coordinate measuring machine in two places on the left and right. Perform binocular stereo matching on the edge of the feature points of the two images. A corner detection algorithm combining SUSAN and Harris is used to detect the left and right camera calibration templates. The two-dimensional coordinate points of the object are determined by the image stereo matching module, and the three-dimensional discrete coordinate points of the object space can be obtained according to the transformation relationship between the image coordinates and the actual object coordinates. Then draw the three-dimensional model of the object through the three-dimensional drawing software. Experimental data shows that the logic resources and memory resources occupied by image preprocessing account for 30.4% and 27.4% of the entire system, respectively. The results show that the system can calibrate the internal and external parameters of the camera. In this way, the camera calibration result will be more accurate and the range will be wider. At the same time, it can effectively make up for the shortcomings of traditional modeling techniques to ensure the measurement accuracy of the detection system.

中文翻译：

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基于3D立体视觉的符号识别系统

随着计算机科学和技术的不断发展，符号识别系统可以从二维空间转换为三维空间。因此，本文主要介绍基于3D立体视觉的符号识别系统。视觉坐标测量机在左右两个位置拍摄三维图像。在两个图像的特征点的边缘执行双目立体匹配。结合SUSAN和Harris的拐角检测算法用于检测左右相机校准模板。物体的二维坐标点由图像立体匹配模块确定，根据图像坐标与实际对象坐标之间的变换关系，可以获得对象空间的三维离散坐标点。然后通过三维绘图软件绘制对象的三维模型。实验数据表明，图像预处理所占用的逻辑资源和内存资源分别占整个系统的30.4％和27.4％。结果表明，该系统可以校准摄像机的内部和外部参数。这样，摄像机的校准结果将更加准确，范围也会更广。同时，可以有效弥补传统建模技术的缺陷，保证检测系统的测量精度。然后通过三维绘图软件绘制对象的三维模型。实验数据表明，图像预处理所占用的逻辑资源和内存资源分别占整个系统的30.4％和27.4％。结果表明，该系统可以校准摄像机的内部和外部参数。这样，摄像机的校准结果将更加准确，范围也会更广。同时，可以有效弥补传统建模技术的缺陷，保证检测系统的测量精度。然后通过三维绘图软件绘制对象的三维模型。实验数据表明，图像预处理所占用的逻辑资源和内存资源分别占整个系统的30.4％和27.4％。结果表明，该系统可以校准摄像机的内部和外部参数。这样，摄像机的校准结果将更加准确，范围也会更广。同时，可以有效弥补传统建模技术的缺陷，保证检测系统的测量精度。占整个系统的4％。结果表明，该系统可以校准摄像机的内部和外部参数。这样，摄像机的校准结果将更加准确，范围也会更广。同时，可以有效弥补传统建模技术的不足，保证检测系统的测量精度。占整个系统的4％。结果表明，该系统可以校准摄像机的内部和外部参数。这样，摄像机的校准结果将更加准确，范围也会更广。同时，可以有效弥补传统建模技术的缺陷，保证检测系统的测量精度。