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Stereo vision blossom mapping for automated thinning in peach

机译:立体视觉开花贴图可自动对桃进行稀疏

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Currently, manual labor is used in the thinning of fruit for ensuring a high yield of marketable fruits. This paper presents ongoing research using a correlation-based stereo vision approach to automated thinning of peach blossoms on perpendicular ‘V’ architecture trees. To this end a calibrated camera system has been designed using three synchronized ten Mpixel cameras and flash illumination. A total station was used to establish blossom ground-truth location. A correlation-based stereo algorithm was developed that is suitable for parallel processing, using multiple camera pairs for validating the correspondence in 3D space, and does not require rectification of the images. The results showed accuracy of less than half of a blossom width (∼ 1cm), provided a good starting point for further development of the algorithm and validated the approach for automated selective blossom thinning application.
机译:当前,人工劳动用于水果稀疏中,以确保可销售的水果的高产量。本文介绍了正在进行的研究,该研究使用基于相关的立体视觉方法对垂直“ V”型建筑树上的桃花进行自动稀疏。为此,已经设计了使用三个同步的十兆像素相机和闪光灯照明的校准相机系统。使用全站仪确定开花地面的真实位置。开发了一种基于相关性的立体算法,该算法适用于并行处理,使用多个摄像机对来验证3D空间中的对应关系,并且不需要对图像进行校正。结果表明,准确度不到开花宽度的一半(〜1cm),为算法的进一步开发提供了良好的起点,并验证了自动选择性开花稀疏应用的方法。

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