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首页> 外文期刊>Journal of electrical and computer engineering >A Curvelet-SC Recognition Method for Maize Disease
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A Curvelet-SC Recognition Method for Maize Disease

机译：玉米病害的Curvelet-SC识别方法

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摘要

Because the corn vein and noise influence the contour extraction of the maize leaf disease, we put forward a new recognition algorithm based on Curvelet and Shape Context (SC). This method can improve the speed and accuracy of maize leaf disease recognition. Firstly, we use Seeded Regional Growing (SRG) algorithm to segment the maize leaf disease image. Secondly, Curvelet Modulus Correlation (CMC) method is put forward to extract the effective contour of maize leaf disease. Thirdly, we combine CMC with the SC algorithm to obtain the histogram features and then use these features we obtain to calculate the similarities between the template image and the target image. Finally, we adopt n-fold cross-validation algorithm to recognize diseases on maize leaf disease database. Experimental results show that the proposed algorithm can recognize 6 kinds of maize leaf diseases accurately and achieve the accuracy of 94.446%. Meanwhile this algorithm has guiding significance for other diseases recognition to an extent.
机译：由于玉米叶脉和噪声影响玉米叶病的轮廓提取，提出了一种基于Curvelet和Shape Context的新识别算法。该方法可以提高玉米叶病识别的速度和准确性。首先，我们使用种子区域生长（SRG）算法对玉米叶片病害图像进行分割。其次，提出了Curvelet模量相关法（CMC）提取玉米叶片病害的有效轮廓。第三，我们将CMC与SC算法结合起来获得直方图特征，然后使用获得的这些特征来计算模板图像和目标图像之间的相似度。最后，我们采用n倍交叉验证算法在玉米叶病数据库上识别疾病。实验结果表明，该算法能准确识别出6种玉米叶病，准确率达到94.446％。同时该算法在一定程度上对其他疾病的识别具有指导意义。

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  • 来源
    《Journal of electrical and computer engineering》 |2015年第2015期|164547.1-164547.8|共8页
  • 作者

    Jing Luo; Shuze Geng; Chunbo Xiu; Dan Song; Tingting Dong;

  • 作者单位

    Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin 300387, China,College of Electrical Engineering and Automation, Tianjin Polytechnic University, Tianjin 300387, China;

    Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin 300387, China,College of Electrical Engineering and Automation, Tianjin Polytechnic University, Tianjin 300387, China;

    Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin 300387, China,College of Electrical Engineering and Automation, Tianjin Polytechnic University, Tianjin 300387, China;

    Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin 300387, China,College of Electrical Engineering and Automation, Tianjin Polytechnic University, Tianjin 300387, China;

    Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin 300387, China,College of Electrical Engineering and Automation, Tianjin Polytechnic University, Tianjin 300387, China;

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