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Determination of quantity and volume of Carya cathayensis Sarg by line laser scanning combined with the point cloud fusion algorithm
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Optical 3D measurement technology plays a vital role in diverse industries, particularly with the advancements in line laser scanning 3D imaging. In this paper, we propose a line laser scanning-based investigation for detecting Carya cathayensis Sarg. The Carya cathayensis Sarg specimens are scanned using a line laser to achieve three-dimensional reconstruction, enabling the calculation of their volume and quantity based on the acquired point cloud map. Through binocular acquisition and subsequent point cloud alignment and fusion, the error in the three-dimensional reconstruction is significantly reduced. The point cloud map facilitates the automatic identification of the number of scanned areas of Carya cathayensis Sarg areas and accurate volume calculations, with an error control of approximately 0.6% when compared to the actual volume. The application of this research in agriculture allows farmers to classify fruit sizes and optimize their selection, thus facilitating intelligent agricultural practices.
Title: Determination of quantity and volume of Carya cathayensis Sarg by line laser scanning combined with the point cloud fusion algorithm
Description:
Optical 3D measurement technology plays a vital role in diverse industries, particularly with the advancements in line laser scanning 3D imaging.
In this paper, we propose a line laser scanning-based investigation for detecting Carya cathayensis Sarg.
The Carya cathayensis Sarg specimens are scanned using a line laser to achieve three-dimensional reconstruction, enabling the calculation of their volume and quantity based on the acquired point cloud map.
Through binocular acquisition and subsequent point cloud alignment and fusion, the error in the three-dimensional reconstruction is significantly reduced.
The point cloud map facilitates the automatic identification of the number of scanned areas of Carya cathayensis Sarg areas and accurate volume calculations, with an error control of approximately 0.
6% when compared to the actual volume.
The application of this research in agriculture allows farmers to classify fruit sizes and optimize their selection, thus facilitating intelligent agricultural practices.
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