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Position: Home > Articles > Apple leaf disease recognition based on feature fusion and local discriminant projection Guangdong Agricultural Sciences 2016,43 (10) 134-139+193

基于特征融合与局部判别映射的苹果叶部病害识别方法

作  者:
李超;彭进业;张善文
单  位:
西北大学信息科学与技术学院;西京学院信息工程学院
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)
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。
译  名:
Apple leaf disease recognition based on feature fusion and local discriminant projection
作  者:
LI Chao;PENG Jin-ye;ZHANG Shan-wen;Department of Information Science and Technology,Northwest University;College of Information Engineering,Xijing University;
关键词:
plant disease recognition;;feature fusion;;adaptive center symmetric local binary pattern (ACS LBP);;support vector machines (SVM);;local discriminant projection (LDP)
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%.

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