复杂背景黄瓜叶部病害图像分割方法
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国家高技术研究发展计划(863计划)资助项目(2013AA102304)和江苏省“六大人才高峰”资助项目(2011-wlw-005)


Segmentation of Cucumber Leaf Disease Images with Complex Background
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    摘要:

    针对具有复杂背景的黄瓜病害图像,设计了一种图像分割方法。该方法首先结合超G和OTSU方法去除彩色图像中的大部分背景,尽可能保留图像中的绿色部分信息;然后根据病害图像RGB模型中红色分量自动建立数据项,并且设定相邻像素间红色分量差值的函数作为平滑项,以上述数据项和平滑项构建基于阈值预处理的图切割算法。利用该方法对4种黄瓜病害(霜霉病、白粉病、靶斑病和炭疽病)彩色图像进行分割。结果表明,该方法能够较为准确地将病斑区域从彩色图像中提取出来,算法的平均正确识别率达到90%以上;平均运行速度为2.12 s,能够满足实时图像分割的要求。

    Abstract:

    A segmentation method of cucumber disease image with complex background was proposed. Firstly, most of the background in color images was removed by combined method of ExG and OTSU, which retained the green part of the image as much as possible. Then, according to the red component of the disease image, the data item was created automatically. Meanwhile, the differences between the red components of adjacent pixels were set as the smooth item. The threshold-pretreatment-based graph cuts algorithm was constructed based on the above data item and smooth item. The proposed method was used to segment the color images of four kinds of cucumber diseases. The results showed that it could better segment the diseased regions from the color images of cucumber diseases. The mean accuracy of recognition was more than 90%, and the average running speed was 2.12 s. The proposed method could meet the requirement of real-time image processing. 

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袁媛,李淼,陈晟,江海洋,董俊.复杂背景黄瓜叶部病害图像分割方法[J].农业机械学报,2013,44(10):233-237. Yuan Yuan, Li Miao, Chen Sheng, Jiang Haiyang, Dong Jun. Segmentation of Cucumber Leaf Disease Images with Complex Background[J]. Transactions of the Chinese Society for Agricultural Machinery,2013,44(10):233-237.

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  • 在线发布日期: 2013-10-14
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