药用植物自动识别与分类研究进展

O. K. Ogidan, A. Onile
{"title":"药用植物自动识别与分类研究进展","authors":"O. K. Ogidan, A. Onile","doi":"10.1201/9780429265204-14","DOIUrl":null,"url":null,"abstract":"Some existing methods for recognizing and classifying medicinal plants are manual, cumbersome, and time-consuming. In this chapter, a comprehensive review of recognition and classification of medicinal plants using Information Communication Technologies (ICT) – Automated Techniques are presented. The study focuses on the recognition and classification of medicinal plant’s leaves using image processing-based and spectroscopic identification techniques. The work reveals that the image processing-based recognition method is more predominant in literature than the spectroscopic method of recognizing medicinal plants. Analysis of previous studies reveals that image processing-based and spectroscopic recognition methods are less cumbersome, faster, and non-destructive when compared to the chemical method. The details of various implementation platforms that are required for effective recognition and classification of medicinal plants are also presented in this chapter. It is believed that with the techniques outlined in this study, more people, including non-experts using electronic devices, would be able to easily recognize and classify medicinal plants. This would offer better insights into their usefulness and conservation for the benefit of the future generation.","PeriodicalId":161277,"journal":{"name":"The Therapeutic Properties of Medicinal Plants","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Automatic Recognition and Classification of Medicinal Plants: A Review\",\"authors\":\"O. K. Ogidan, A. Onile\",\"doi\":\"10.1201/9780429265204-14\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Some existing methods for recognizing and classifying medicinal plants are manual, cumbersome, and time-consuming. In this chapter, a comprehensive review of recognition and classification of medicinal plants using Information Communication Technologies (ICT) – Automated Techniques are presented. The study focuses on the recognition and classification of medicinal plant’s leaves using image processing-based and spectroscopic identification techniques. The work reveals that the image processing-based recognition method is more predominant in literature than the spectroscopic method of recognizing medicinal plants. Analysis of previous studies reveals that image processing-based and spectroscopic recognition methods are less cumbersome, faster, and non-destructive when compared to the chemical method. The details of various implementation platforms that are required for effective recognition and classification of medicinal plants are also presented in this chapter. It is believed that with the techniques outlined in this study, more people, including non-experts using electronic devices, would be able to easily recognize and classify medicinal plants. This would offer better insights into their usefulness and conservation for the benefit of the future generation.\",\"PeriodicalId\":161277,\"journal\":{\"name\":\"The Therapeutic Properties of Medicinal Plants\",\"volume\":\"82 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Therapeutic Properties of Medicinal Plants\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1201/9780429265204-14\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Therapeutic Properties of Medicinal Plants","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1201/9780429265204-14","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

现有的药用植物识别和分类方法手工、繁琐、耗时。本章综述了利用信息通信技术(ICT)自动化技术对药用植物进行识别和分类的研究进展。研究了基于图像处理和光谱识别技术对药用植物叶片的识别与分类。研究表明,基于图像处理的药用植物识别方法在文献中比光谱识别方法更占优势。分析以往的研究表明,与化学方法相比,基于图像处理和光谱识别的方法更简单、更快、无损。本章还详细介绍了有效识别和分类药用植物所需的各种实施平台。相信有了本研究中概述的技术,更多的人,包括使用电子设备的非专家,将能够轻松识别和分类药用植物。这将更好地了解它们的用途和保护,造福后代。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Recognition and Classification of Medicinal Plants: A Review
Some existing methods for recognizing and classifying medicinal plants are manual, cumbersome, and time-consuming. In this chapter, a comprehensive review of recognition and classification of medicinal plants using Information Communication Technologies (ICT) – Automated Techniques are presented. The study focuses on the recognition and classification of medicinal plant’s leaves using image processing-based and spectroscopic identification techniques. The work reveals that the image processing-based recognition method is more predominant in literature than the spectroscopic method of recognizing medicinal plants. Analysis of previous studies reveals that image processing-based and spectroscopic recognition methods are less cumbersome, faster, and non-destructive when compared to the chemical method. The details of various implementation platforms that are required for effective recognition and classification of medicinal plants are also presented in this chapter. It is believed that with the techniques outlined in this study, more people, including non-experts using electronic devices, would be able to easily recognize and classify medicinal plants. This would offer better insights into their usefulness and conservation for the benefit of the future generation.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信