[1]赵熙临,单治磊,付波,等.应用叶片图像分割与特征融合的复杂背景植物识别方法[J].华侨大学学报(自然科学版),2018,39(2):274-280.[doi:10.11830/ISSN.1000-5013.201706075]
　ZHAO Xilin,SHAN Zhilei,FU Bo,et al.Research of Plant Recognition Using Segmentation and Feature Fusion[J].Journal of Huaqiao University(Natural Science),2018,39(2):274-280.[doi:10.11830/ISSN.1000-5013.201706075]
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应用叶片图像分割与特征融合的复杂背景植物识别方法()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第39卷
期数:
2018年第2期
页码:
274-280
栏目:
出版日期:
2018-03-20

文章信息/Info

Title:
Research of Plant Recognition Using Segmentation and Feature Fusion
文章编号:
1000-5013(2018)02-0274-07
作者:
赵熙临;  单治磊;  付波;  杨章
湖北工业大学 电气与电子工程学院, 湖北 武汉 430068
Author(s):
ZHAO Xilin;  SHAN Zhilei;  FU Bo;  YANG Zhang
School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China
关键词:
植物叶片;  图像分割;  复杂背景;  标志分水岭算法;  形态学变换
Keywords:
plant leaf;  image segmentation;  complex background;  segmentation algorithm;  morphological transformation
分类号:
TP391.4
DOI:
10.11830/ISSN.1000-5013.201706075
文献标志码:
A
摘要:
针对复杂背景的存在性,通过图像分割处理消除复杂背景因素对植物识别的负面影响.提出一种基于形态学变换的标记分水岭算法,对植物叶片进行重建的开闭操作,并使用标记分水岭算法对其进行分割.识别测试纹理与形状特征提取方式,了解图像分割算法对复杂背景消除的有效性.结果表明:提出的算法能有效分割复杂背景叶片.
Abstract:
Considering of the existence of complex background, the negative effects of complex background factors on leaves recognition are eliminated by image segmentation. At the same time, a segmentation algorithm be founded on morphological transform is proposed to solve the over-segmentation problem in the segmentation of plant leaves. After the opening and closing based on the reconstruction, the plant leaves are segment by marker-watershed algorithm. The texture and shape features, extracted form the segmented leaves, are used to recognize the leaves. And the effectiveness of the recognition validates that the segmentation algorithm proposed in this paper is effective.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2017-06-26
通信作者: 赵熙临(1969-),男,副教授,博士,主要从事电力系统及自动化、先进控制理论的研究.E-mail:zhaoxilin@mail.hbut.edu.cn.
基金项目: 国家自然科学基金资助项目(61072130); 国家教育部科研项目(教外司留20041685); 湖北省科技厅重大专项项目(2013AEA001)
更新日期/Last Update: 2018-03-20