植物叶图像特征分析和分类检索  

Automatic image classification and retrieval by analyzing plant leaf features

作　　者：姚飞[1] 叶康[2] 周坚华[3] 

机构地区：[1]华东师范大学地理科学学院,上海200241 [2]上海植物园科研中心,上海200231 [3]华东师范大学地理信息科学教育部重点实验室,上海200241

出　　处：《浙江农林大学学报》2015年第3期426-433,共8页Journal of Zhejiang A&F University

基　　金：国家自然科学基金资助项目(41071275);国家理科基地科研训练及科研能力提高项目(J1310028)

摘　　要：研究基于植物叶特征的植物属种自动图像分类检索技术。为了解决植物属种众多引起的分类困难,综合应用了图像分类和图像检索的一些概念模型和方法,如根据图像检索概念,构建以叶形和叶缘特征变化为依据的阔叶类植物(单叶)分类语义字典;根据图像分类原理,设计字典各层分支结点的描述符;根据相似概率索引方法,推求字典叶节点成员属于特定植物种的概率,进而实现对植物属种做图像分类索引的功能。以适量样本所做的分类实验表明:面积凹凸比、长宽比、右边界非线性拟合二次项系数、上边界非线性拟合二次项系数、最宽处位置指数等描述符对于阔叶植物分类有效。通过这些描述符可以将31类阔叶植物划分到8个叶节点,并检索其具体属种;全局分类精度平均为94.19%。并初步证明了如下结论:"分类语义字典组织的分层分类+叶节点成员相似性检索"的技术框架,可以有效扩大植物属种辨识数量、提高辨识精度,是植物数字搜索引擎合理有效的概念模型。The o bjective of this article is to present a novel conceptual framework for discerning tree species from plant leaf digital images and to assess its applicability. In order to make huge numbers of plant species discernable, some concepts and methodologies of image classification and retrieval were comprehensively and innovatively employed in this framework. For example, according to the concept of image retrieval, a semantic dictionary for partitioning broad-leaf plants was created based on the differences between species in leaf shape and leaf margin. Each sample plant was represented by the images photographed from one of its leaves. By following principles of image classification, several descriptors for each splitting node in the semantic dictionary were designed and tested. Then, by imitating the retrieval method, the similarity probability, which means the probability that a new node member belonged to a certain plant species, could be properly assessed through calculating the variance of attribute between the new one and the known plant species. Finally, the objective mentioned before could be achieved. The classification results revealed that all newly explored descriptors,such as the area ratio of leaf patch to its convex hull, the length to width ratio, the second-order fitting coeffi-cient of the leaf edge, and the location index of the widest site of a leaf were applicable to classification of broad-leaf plant species and high classification accuracy could be expected with some example combinations of them. Altogether, 31 plant species were classified into eight leaf nodes, and then their specific species were determined quite accurately by assessing the similarity probability. The overall classification accuracy assessed by confusion matrix method was usually better than 94.2%. These results verified that the conceptual framework combining image classification and retrieval was reasonable, effective, and accurate for discerning plant species from digital leaf images.

关 键 词：植物学 植物叶片特征 语义字典 分层分类 描述符 图像索引 

分 类 号：S758.5[农业科学—森林经理学]