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Research on weed recognition method based on invariant moments

机译:基于不变矩的杂草识别方法研究

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A new method of weed recognition based on the invariant moments was proposed in this paper. Firstly, the area of the soybean leaf was located from the complicated image background. Secondly, the features of soybean leaf were obtained by Hu invariant moments, which are the invariability of the translation, the ratio and the rotation, and have lower computational complexity. Finally, the soybean leaf was recognized by the nearest neighbor classifier, and other image information were identified to weed. Experimental results proved that the weed recognition method was effective on the different environment, and could location the weed rapidly, reliably and accurately. The correct rate of the weed recognition was 90.5% in the ordinary environment, the average cost time was 670ms.
机译:提出了一种基于不变矩的杂草识别新方法。首先,从复杂的图像背景中定位了大豆叶的区域。其次,利用Hu不变矩获得了大豆叶片的特征,即平移,比例和旋转不变,并且计算复杂度较低。最后,大豆叶被最近的邻居分类器识别,并识别了其他图像信息以除草。实验结果表明,该杂草识别方法在不同环境下均有效,能够快速,可靠,准确地定位杂草。在正常环境下,杂草识别的正确率为90.5%,平均花费时间为670ms。

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