计算机工程与应用 ›› 2017, Vol. 53 ›› Issue (2): 162-165.DOI: 10.3778/j.issn.1002-8331.1504-0233

• 模式识别与人工智能 • 上一篇    下一篇

基于形状特征的植物叶片在线识别方法

李  洋1,李岳阳2,罗海驰1,蒋高明2,丛洪莲2   

  1. 1.江南大学 轻工过程先进控制教育部重点实验室,江苏 无锡 214122
    2.江南大学 经编技术教育部工程研究中心,江苏 无锡 214122
  • 出版日期:2017-01-15 发布日期:2017-05-11

 Online plant left recognition based on shape features

LI Yang1, LI Yueyang2, LUO Haichi1, JIANG Gaoming2, CONG Honglian2   

  1. 1.Ministry of Education Key Laboratory of Advanced Process Control for Light Industry, Jiangnan University, Wuxi, Jiangsu 214122, China
    2.Engineering Research Center of Warp Knitting Technology Ministry of Education, Jiangnan University, Wuxi, Jiangsu 214122, China
  • Online:2017-01-15 Published:2017-05-11

摘要: 针对传统植物识别方法工作任务量大,效率低下以及难以保证数据客观性的问题,提出了一种基于形状特征的植物叶片识别算法,并开发了一款C/S模式的植物叶片在线识别Android应用。叶片图像经预处理后,提取叶片的轮廓凸包顶点比、轮廓曲率方差等形状特征,采用KNN-SVM对叶片进行分类识别。实验结果表明,相比于一些已有识别算法,该算法可以达到更高的识别率;该Android应用稳定可靠,可以满足用户的需求。

关键词: 叶片识别, 形状特征, Android, [K]近邻算法-支持向量机(KNN-SVM)

Abstract: As to the problems of traditional plant recognition methods for heavy workload, inefficiency and hard to guarantee the objectivity of the data, a plant leaf recognition algorithm based on shape features is presented and an Android application of online plant leaf recognition based on C/S model is developed in this paper. Firstly, the leaf image is preprocessed to get the leaf contour. Then, the traditional shape features and two new ones, the contour convex ratio for plant leaf and the variance of contour curvature, are extracted. Finally, the plant is recognized by using KNN-SVM. Experimental results show that the higher recognition rate can be obtained by using the proposed method compared to some existing algorithms. Also the Android application is stable and reliable for user’s requirement.

Key words: plant recognition, shape features, Android, K-Nearest Neighbor-Support Vector Machine(KNN-SVM)