| 李 超1，彭进业1，张善文2.基于特征融合与局部判别映射的苹果叶部病害识别方法[J].广东农业科学,2016,43(10):134-139 |
|
查看全文
HTML
基于特征融合与局部判别映射的苹果叶部病害识别方法 |
| Apple leaf disease recognition based on feature fusion and local discriminant projection |
| |
| DOI：10.16768/j.issn.1004-874X.2016.10.024 |
| 中文关键词: 植物病害识别 特征融合 自适应中心对称局部二值模式（ACS-LBP） 支持向量机（SVM） 改进局部判别映射（LDP） |
| 英文关键词: plant disease recognition feature fusion adaptive center symmetric local binary pattern（ACSLBP） support vector machines（SVM） local discriminant projection（LDP） |
| 基金项目:国家自然科学基金 (61473237)；陕西省教育厅自然科学研究项目（2013JK887） |
|
| 摘要点击次数: 1858 |
| 全文下载次数: 794 |
| 中文摘要: |
| 针对利用植物病害叶片图像特征识别病害类别的复杂性，提出一种基于特征融合与局部判别
映射的植物叶部病害识别方法。首先，在中心对称局部二值模式（CS-LBP）的基础上，设计了一种自适应
中心对称局部二值模式（ACS-LBP），由此分割病害叶片的病斑图像；然后提取并融合病斑图像的纹理、形
状和颜色特征；再利用局部判别映射算法对融合特征进行维数约简；最后利用支持向量机进行病害类别分
类。在3种常见苹果病害叶片图像数据库上进行病害识别验证试验，结果表明，该方法能够有效识别苹果
叶部病害，平均识别率高达96%以上。 |
| 英文摘要: |
| As for the complexity of plant disease recognition by the disease leaf image，a plant disease
recognition method was proposed based on feature fusion and local discriminant projection. First，based on the center
symmetric local binary pattern（CS-LBP），an adaptive CS-LBP algorithm was proposed. The spot images were
segmented by ACS-LBP. The texture，shape and color features were extracted from each spot image and fused，and
then were reduced based on local discriminant projection（LDP）. Finally，the diseases were recognized by support
vector machine（SVM）. The experiment results on a database of apple disease leaf images showed that the proposed
method was effective for apple leaf disease recognition. The average recognition rate was more than 95%. |
|
查看/发表评论 下载PDF阅读器 |
