基于多特征融合的植物叶片识别研究  

Plant leaf recognition based on fusion of multiple features

作　　者：高良[1] 闫民[2] 赵方[1] 

机构地区：[1]北京林业大学信息学院,北京100083 [2]北京林业大学工学院,北京100083

出　　处：《浙江农业学报》2017年第4期668-675,共8页Acta Agriculturae Zhejiangensis

基　　金：国家自然科学基金项目(11272061)

摘　　要：植物叶片识别作为植物自动分类识别的重要分支,有着很高的实际应用价值。针对当前叶片特征描述存在的局限和叶片识别准确率较低的实际,以叶片图像为研究对象,首先对图像进行预处理,在提取叶片几何特征和纹理特征的基础上,设计描述叶片轮廓的距离矩阵和角点矩阵,通过计算基于几何特征、纹理特征和角点距离矩阵的综合相似度对叶片进行精确识别。对Flavia数据集中的32类共计960幅叶片图像进行训练和测试,结果表明,基于叶片图像多特征融合的识别方法对叶片特征描述能力更强,识别准确率更高,对Flavia数据集的识别率可达97.50%,具有较好的识别效果。As an important branch of plant automatic classification and recognition, plant leaf recognition is of great value in practical application. In view of the limitation of description methods for leaf features and the problem of low accuracy of plant leaf recognition, leaf images were used as recognition objects in this paper. An image preprocessing algorithm was proposed to ensure getting the features of leaf images accurately. In addition to the geometric features and texture features, the leaf profile was described by distance matrix and corner matrix, and the leaf could be identi-fied more precisely by calculating the comprehensive similarity of geometric features, texture features and corner dis-tance matrix. Experiments were performed on Flavia dataset of 960 images divided into 32 classes. Compared with other recognition methods, the method proposed in this paper achieved better recognition effect. The experimental re-sults showed that the recognition accuracy reached 97. 50% with high practicability.

关 键 词：叶片识别 几何特征 纹理特征 角点距离矩阵 综合相似度 

分 类 号：S126[农业科学—农业基础科学]