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An automatic method for identifying different variety of rice seeds using machine vision technology

机译:利用机器视觉技术自动识别不同水稻种子的方法

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An automatic method for identifying different variety of rice seeds using machine vision technology will be investigated and its system, consisting of an automatic inspection machine and an image-processing unit, was also developed. The system could continually present matrix-positioned rice seed to CCD cameras, singularize each rice seed image from the background. The inspection machine had scattering and positioning devices, a photographing station, a parallel discharging device, and a continuous conveyer belt with carrying holes for the rice seed. The rice seeds' image was achieved continuously by single chip controlled device. The line was stopped every one second for one second by the device. The camera took an image of simple seed when it stopped. Image analysis was carried out programmed by Visual C++ 6.0. Color features in RGB (red, green, blue) and color spaces were computed. A back-forward neural network was trained to identify rice seeds. Almost all 86.65% rice seeds were correctly identified. The correct classification rates for five rice varieties were: No.5 'Xiannong' of 99.99%, 'Jinyougui' of 99.93%,'You166' of 98.89%, No. 3 'Xiannong' of 82.82% and 'Medium you' 463 of 86.65%, respectively. Based on the results, it was concluded that the system was enough to use for inspection of varieties of different rice seed based on its appearance characters of seeds.
机译:将研究一种使用机器视觉技术识别不同水稻种子的自动方法,并开发了由自动检查机和图像处理单元组成的系统。该系统可以连续将矩阵定位的水稻种子呈现给CCD摄像机,从背景中将每个水稻种子图像进行单数化处理。该检查机具有散射和定位装置,照相台,平行排出装置以及带有用于稻种的输送孔的连续输送带。水稻种子的图像是通过单片机控制的设备连续获得的。该设备每秒钟将生产线停止一秒钟。相机停下时拍摄了简单种子的图像。图像分析是通过Visual C ++ 6.0编程进行的。计算了RGB(红色,绿色,蓝色)和色彩空间中的色彩特征。训练了反向神经网络来识别水稻种子。几乎所有86.65%的水稻种子均已正确鉴定。五个水稻品种的正确分类率分别为:“仙农”第5位为99.99%,“金油桂”为99.93%,“优166”为98.89%,第3位“仙农”为82.82%和“中油” 463。分别为86.65%。根据结果​​得出结论,该系统根据其种子的外观特性,足以用于检查不同水稻种子的品种。

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