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Weight Estimation of Mango from Single Visible Fruit Surface using Computer Vision

机译:使用计算机视觉从单个可见水果表面估计芒果的重量

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This paper presents the development of an image processing algorithm to estimate the weight and volume of the mango. In this study, a total of 24 mangoes are used as samples. On account of simplicity, only a single web camera is used to capture the top view image of the mango. From this image, geometric features of the mango such as area, width and length are evaluated. Area of the mango's visible surface is determined by using curve fitting and area between the two curves method. Thickness of the mango, which is not visible in top view image, is necessary to estimate weight and volume more accurately. The required thickness value is calculated from the correlation equation between width and thickness. The thickness variation along the mango length is modelled as an ellipse function. The total estimated volumes of the mango is calculated by using the sum of volumes of transverse sectional elliptic cylinders method. The estimated results are compared with actual measured values. The average accuracy of this algorithm is 95% for both volume and weight estimation. Average processing time for each mango is 0.2 seconds.
机译:本文提出了一种估计芒果重量和体积的图像处理算法的开发。在这项研究中,总共使用了24种芒果作为样品。为简单起见,仅使用一个网络摄像头捕获芒果的顶视图图像。根据该图像,可以评估芒果的几何特征,例如面积,宽度和长度。芒果可见表面的面积是通过曲线拟合和两条曲线之间的面积确定的。芒果的厚度(在顶视图图像中不可见)对于更准确地估计重量和体积是必需的。根据宽度和厚度之间的相关方程计算所需的厚度值。沿芒果长度的厚度变化被建模为椭圆函数。芒果的总估计体积通过使用横截面椭圆圆柱体的体积总和方法计算得出。将估计结果与实际测量值进行比较。对于体积和重量估算,此算法的平均准确度均为95%。每个芒果的平均处理时间为0.2秒。

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