| 张善文， 黄文准， 师 韵.基于改进Bernsen 二值化算法的
植物病害叶片病斑检测[J].广东农业科学,2016,43(12):129-133 |
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基于改进Bernsen 二值化算法的
植物病害叶片病斑检测 |
| Improved Bernsen binary algorithm fordetection of plant disease leaves |
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| DOI：10.16768/j.issn.1004-874X.2016.12.022 |
| 中文关键词: 病斑检测 农业物联网 Bernsen 算法 改进Bernsen 算法 |
| 英文关键词: lesion detection agricultural IOT Bernsen algorithm improved Bernsen algorithm |
| 基金项目:国家自然科学基金（61473237）；陕西省自然科学基础研究计划项目（2014JM2-6096） |
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| 摘要点击次数: 2022 |
| 全文下载次数: 1099 |
| 中文摘要: |
| 针对大区域田间复杂背景下植物病害远程识别中的叶片病斑检测难问题，提出一种基于改进
Bernsen 二值化算法的植物病害远程检测方法。通过物联网采集不同区域的植物叶片图像，根据在RGB 和
HIS 颜色空间中叶片病斑与正常叶片和背景的色调差异的特点，利用改进Bernsen 二值化算法分别在图像
的R、G、B、H 4 个颜色通道上提取病斑，然后进行病斑图像融合，得到病斑图像。采用该方法对多幅物联
网视频植物病害叶片图像进行病斑分割。实验结果表明，该算法在复杂背景环境下能够有效分割植物病斑
图像，去除大量复杂背景，得到病斑图像。该方法能够为大区域植物病害远程智能监控系统提供技术指导。 |
| 英文摘要: |
| As for the diffcultity of leaf spot disease detection in plant remote identification under complex
background of large field，a remote detection method of plant disease was proposed based on improved Bernsen
binary algorithm. The disease leaf images were collected by IOT from different areas. According to the different
characteristics of color subspace of RGB and HIS of disease leaf and normal leaf and background colors，the spot
images were extracted by the improved Bernsen binary algorithm from the four color channels of R，G，B and H，
respectively. Then the spot images were obtained by spot image fusion. The proposed method was applied to segment
several plant disease leaf images of agricultural IOT. Results showed that the improved algorithm could effectively
segment the plant disease images in the complex background environment，remove a large complex background，
and obtain the spot image. The proposed method can provide technical guidance for the remote intelligent monitoring
system of plant disease in large areas. |
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