[1]谢泽奇,张会敏,张善文,等.基于颜色特征和属性约简的黄瓜病害识别方法[J].江苏农业学报,2015,(03):526-530.[doi:10.3969/j.issn.1000-4440.2015.03.010]
 XIE Ze-qi,ZHANG Hui-min,ZHANG Shan-wen,et al.Cucumber disease recognition based on color feature and attribute reduction[J].,2015,(03):526-530.[doi:10.3969/j.issn.1000-4440.2015.03.010]
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基于颜色特征和属性约简的黄瓜病害识别方法()
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江苏农业学报[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2015年03期
页码:
526-530
栏目:
植物保护
出版日期:
2015-06-30

文章信息/Info

Title:
Cucumber disease recognition based on color feature and attribute reduction
作者:
谢泽奇张会敏张善文张云龙
(郑州大学西亚斯国际学院,河南郑州451150)
Author(s):
XIE Ze-qiZHANG Hui-minZHANG Shan-wenZHANG Yun-long
(SIAS International University, Zhengzhou University, Zhengzhou 451150, China)
关键词:
颜色特征属性约简病斑分割病害识别
Keywords:
color featureattribute reductionimage segmentationdisease recognition
分类号:
TP391
DOI:
10.3969/j.issn.1000-4440.2015.03.010
文献标志码:
A
摘要:
为了减少黄瓜叶部病害给农业生产带来的损失,提高病害的识别率和精度,提出了一种基于颜色特征和属性约简算法的黄瓜病害叶片分割与识别方法。该方法首先利用最大类间方差(Otsu)阈值法对黄瓜病害叶片图像进行病斑分割;其次提取病斑图像的36个分类特征,再利用基于区分矩阵的属性约简算法进行特征选择;最后利用最近邻分类器进行病害识别。该方法在5种常见黄瓜病害叶片图像数据库上进行了病害识别试验,结果表明,识别率高达 94.8%。说明,该方法对作物病害叶片图像识别是有效可行的。
Abstract:
To reduce the loss caused by cucumber leaf disease, and improve disease recognition rate and accuracy, a leaf image segmentation and disease recognition method for cucumber was proposed based on color feature and attribute reduction algorithm. Firstly, the Otsu algorithm was applied to segment the cucumber diseased leaf image. Secondly, 36 diagnostic characters of disease lesion were extracted, and selected by using attribute reduction algorithm based on discernibility matrix. Finally, the crop diseases were recognized using the nearest neighbor classifier. As an effective and feasible approach for crop disease recognition, this method could recognize as high as 94.8% of five cucumber diseases.

参考文献/References:


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备注/Memo

备注/Memo:
收稿日期:2014-11-19 基金项目:国家自然科学基金项目(61272333);河南省科技厅科技攻关项目(142102310518、142400410853、142300410309);河南省教育厅科学技术研究重点项目(14B520064、15A520100);郑州大学西亚斯国际学院校级科研项目(2014KYYB23) 作者简介:谢泽奇(1981-),男,河南镇平人,硕士,讲师,研究方向为计算机应用、图像处理。(E-mail)xzq0413@163.com 通讯作者:张会敏,(E-mail)zhm0413@163.com
更新日期/Last Update: 2015-06-30