| 基于MDMP-LSM算法的黄瓜叶片病斑分割方法 |
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| 引用本文： | 江海洋,张 建,袁 媛,何绵涛,郑守国.基于MDMP-LSM算法的黄瓜叶片病斑分割方法[J].农业工程学报,2012,28(21):142-148. |
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| 作者姓名： | 江海洋 张 建 袁 媛 何绵涛 郑守国 |
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| 作者单位： | 1. 中国科学技术大学信息科学技术学院,合肥 230026
2. 中国科学院合肥智能机械研究所,合肥 230031 |
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| 基金项目： | 国家863项目（2011AA100704） |
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| 摘 要： | 在复杂背景中有效分割作物病斑是解决作物病害识别的关键问题。针对这一问题,该文提出了一种全新的多域多相水平集方法。利用病斑在空间位置上处于叶片轮廓内的特点,构造出基于内部顺序的多相水平集模型。为了加强该模型对复杂背景下作物叶片病斑的分割能力,首次在该模型中引入多个空间域,构造出新的多域多相水平集模型,使内外水平集函数分别在不同空间域中进行演化。试验结果平均分割准确率为93.3%,较好地从复杂背景图片中提取出病斑,为病害诊断奠定了基础。
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| 关 键 词： | 图像分割 作物 病害 水平集方法 多域多相 复杂背景 |
| 收稿时间： | 2012/5/12 0:00:00 |
| 修稿时间： | 2012/10/10 0:00:00 |
Segmentation of cucumber disease leaf image based on MDMP-LSM |
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| Jiang Haiyang,Zhang Jian,Yuan Yuan,He Miantao and Zheng Shouguo.Segmentation of cucumber disease leaf image based on MDMP-LSM[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(21):142-148. |
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| Authors: | Jiang Haiyang Zhang Jian Yuan Yuan He Miantao and Zheng Shouguo |
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| Institution: | 1. School of Information Science and Technology, University of Science and Technology of China, Hefei 230026, China; 2. Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China) |
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| Abstract: | It is a crucial problem for crop disease diagnosing to effectively extract disease spots from crop pictures with complex background. To solve this problem, a new multiple domain multiple phase level set method is proposed. First, the spatial distribution characteristic that the disease spots to be segmented are statistically located in inner parts of crop leaves is adopted to build a multiple phase level set model with inner ordering. Then, to enhance segmentation effectivity for complex background cases, we adopt multiple spatial domains to the model for the first time so that inner and outer level set functions will evolve in different spatial domains. Experimental results show that this method can well extract disease spots for complex background cases with an accuracy rate of 93.3% and will be a good base for diagnoses. |
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| Keywords: | image segmentation crops diseases level set method multiple domain multiple phase complex background |
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