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Machine vision inspection of rice seed based on Hough transform

机译:基于霍夫变换的水稻种子机器视觉检测

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A machine vision system was developed to inspect the quality of rice seeds. Five varieties of Jinyou402,Shanyou 10, Zhongyou207, Jiayou and Ilyou were evaluated. The images of both sides of rice seed with black background and white background were acquired with the image processing system for identifying external features of rice seeds. Five image sets consisting of 600 original images each were obtained. Then a digital image processing algorithm based on Hough transform was developed to inspect the rice seeds with incompletely closed glumes. The algorithm was implemented with all image sets using a Matlab 6.5 procedure. The results showed that the algorithm achieved an average accuracy of 96% for normal seeds, 92% for seeds with fine fissure and 87% for seeds with incompletely closed glumes. The algorithm was proved to be applicable to different seed varieties and insensitive to the color of the background.
机译:开发了机器视觉系统以检查稻米种子的质量。评价了金优402,山优10,中优207,佳优和一优五个品种。利用图像处理系统获取了具有黑色背景和白色背景的水稻种子两面的图像,以识别水稻种子的外部特征。获得了五个图像集,每个图像集包含600个原始图像。然后,开发了一种基于霍夫变换的数字图像处理算法,以检测不完全闭合颖片的水稻种子。使用Matlab 6.5程序对所有图像集实施了该算法。结果表明,该算法对普通种子的平均准确度为96%,对于细裂种子的平均准确度为92%,对于不完全闭合颖片的种子的平均准确度为87%。证明该算法适用于不同的种子品种,并且对背景颜色不敏感。

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