计算机应用与软件2017，Vol.34Issue(9)：222-227,6.DOI:10.3969/j.issn.1000-386x.2017.09.044
基于整体外观特征的植物种类识别研究
THE PLANT SPECIES RECOGNITION BASED ON THE WHOLE APPEARANC FEATURES
陈淑君 1周永霞 1方勇军2
作者信息
- 1. 中国计量大学信息工程学院 浙江杭州310018
- 2. 杭州吾思智能科技有限公司 浙江杭州310018
- 折叠
摘要
Abstract
In this paper,we propose an algorithm for plant species recognition based on whole appearance features.First,the Spectral Residual method was adopted in salient region detection to segment the plant object roughly.And then,the hue information was used to obtain the precise object.Second,SIFT in the object region was extracted to build the BOV model.Finally,three classifiers were designed and implemented to classify the plant species.In our experiments,there were nine different plant species,and 28 examples of each species.BP neural network,SVM and ELM,these three different classifiers were implemented and compared.The experimental results show that the SVM and ELM classifiers were better than BP neural network,and are able to identify about 90％ of these plants correctly.It is important for the research and application of plant species recognition.关键词
普残差法/SIFT/视觉词包模型/支持向量机/极限学习机Key words
Spectral residual/SIFT/Bag-of-visterms/Support vector machine/Extreme learning machine分类
信息技术与安全科学引用本文复制引用
陈淑君,周永霞,方勇军..基于整体外观特征的植物种类识别研究[J].计算机应用与软件,2017,34(9):222-227,6.
