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首页> 外文会议>Conference on Biological Quality and Precision Agriculture II, Nov 6-8, 2000, Boston, USA >Application of machine vision in inspecting stem and shape of fruits
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Application of machine vision in inspecting stem and shape of fruits

机译：机器视觉在水果茎和形状检测中的应用

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The shape and the condition of stem are important features in classification of Huanghua pears. As the commonly used thinning and erosion-dilation algorithm in judging the presence of the stem is too slow, a new fast algorithm was put forward. Compared with other part of the pear, the stem is obviously thin and long, with the help of various sized templates, the judgment of whether the stem is present was easily made, meanwhile the stem head and the intersection point of stem bottom and pear were labeled. Furthermore, after the slopes of the tangential line of stem head and tangential line of stem bottom were found, the included angle of these two lines was calculated. It was found that the included angle of the broken stem was obviously different from that of the good stem. After the analysis of 53 pictures of pears, the accuracy to judge whether the stem is present is 100% and whether the stem is good reaches 93%. Also, the algorithm is of robustness and can be made invariant to translation and rotation. Meanwhile, the method to describe the shape of irregular fruits was studied. Fourier transformation and inverse Fourier transformation pair were adopted to describe the shape of Huanghua pears, and the algorithm for shape identification, which was based on artificial neural network, was developed. The first sixteen harmonic components of the Fourier descriptor were enough to represent the primary shape of pear, and the identification accuracy could reach 90% by applying the Fourier descriptor in combination with artificial neural network.
机译：茎的形状和状况是黄hua梨分类的重要特征。由于在判断茎干存在时常用的稀疏和侵蚀-膨胀算法太慢，提出了一种新的快速算法。与梨的其他部分相比，茎明显较细且长，借助各种尺寸的模板，可以轻松判断是否存在茎，同时可以确定茎头和茎底与梨的交点。标记。此外，在找到杆头切线和杆底切线的斜率后，计算了这两条线的夹角。结果发现，断茎的夹角与良茎的夹角明显不同。经过对53张梨子图片的分析，判断茎是否存在的准确度为100％，茎是否良好为93％。而且，该算法具有鲁棒性，并且可以使其平移和旋转不变。同时，研究了描述不规则果实形状的方法。采用傅立叶变换和傅立叶逆变换对描述黄花梨的形状，并开发了基于人工神经网络的形状识别算法。傅里叶描述子的前16个谐波分量足以代表梨的主要形状，结合使用傅里叶描述子和人工神经网络，识别精度可以达到90％。

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