{"title":"海藻(Neomeris vanbosseae ma .A. Howe)的自动识别框架:U3S","authors":"Ching Soon Tan, P. Lau, S. Phang, Tang Jung Low","doi":"10.1109/ICCOINS.2014.6868360","DOIUrl":null,"url":null,"abstract":"Neomeris vanbosseae M.A. Howe (NVH) is an algae belonging to the Chlorophyta, which is a very diverse group of algae. Therefore when an algae biologist establishes an abundance assessment for algae biodiversity, the taxonomic identification and quantification could frequently lead to a time intensive procedure which is prone to a counting bias, due to fatigue when processing large pools of data samples repeatedly. To improve the effectiveness, this paper proposed a framework, being an assistive tool, to help marine biologists. The framework consists of (1) pre-processing the image, (2) segmenting region of interest, (3) extracting features (namely four different geometric features), (4) evaluating and combining those features based on the given decision criterions, and (5) the quantification. Our methodology achieved satisfactory performance (NVH abundance) as it's able to provide an encouraging result with 78.38% detection rate yielded by the comparison between manual count and our system automatic count. The major contribution of this work is the development and the deployment of an automatic identification system, named U3S, for biodiversity abundance studies of algae to assist the marine biologist in identifying algae species, complementing the existing operator intensive procedures.","PeriodicalId":368100,"journal":{"name":"2014 International Conference on Computer and Information Sciences (ICCOINS)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"A framework for the automatic identification of algae (Neomeris vanbosseae M.A. Howe):U3S\",\"authors\":\"Ching Soon Tan, P. Lau, S. Phang, Tang Jung Low\",\"doi\":\"10.1109/ICCOINS.2014.6868360\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Neomeris vanbosseae M.A. Howe (NVH) is an algae belonging to the Chlorophyta, which is a very diverse group of algae. Therefore when an algae biologist establishes an abundance assessment for algae biodiversity, the taxonomic identification and quantification could frequently lead to a time intensive procedure which is prone to a counting bias, due to fatigue when processing large pools of data samples repeatedly. To improve the effectiveness, this paper proposed a framework, being an assistive tool, to help marine biologists. The framework consists of (1) pre-processing the image, (2) segmenting region of interest, (3) extracting features (namely four different geometric features), (4) evaluating and combining those features based on the given decision criterions, and (5) the quantification. Our methodology achieved satisfactory performance (NVH abundance) as it's able to provide an encouraging result with 78.38% detection rate yielded by the comparison between manual count and our system automatic count. The major contribution of this work is the development and the deployment of an automatic identification system, named U3S, for biodiversity abundance studies of algae to assist the marine biologist in identifying algae species, complementing the existing operator intensive procedures.\",\"PeriodicalId\":368100,\"journal\":{\"name\":\"2014 International Conference on Computer and Information Sciences (ICCOINS)\",\"volume\":\"113 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Computer and Information Sciences (ICCOINS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCOINS.2014.6868360\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Computer and Information Sciences (ICCOINS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCOINS.2014.6868360","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
摘要
Neomeris vanbosseae M.A. Howe (NVH)是一种藻类,属于绿藻,这是一个非常多样化的藻类群。因此,当藻类生物学家建立藻类生物多样性丰度评估时,由于重复处理大量数据样本时的疲劳,分类鉴定和定量往往会导致时间密集的过程,并且容易产生计数偏差。为了提高效率,本文提出了一个框架,作为一个辅助工具,以帮助海洋生物学家。该框架包括(1)对图像进行预处理,(2)对感兴趣区域进行分割,(3)提取特征(即四种不同的几何特征),(4)根据给定的决策准则对这些特征进行评估和组合,以及(5)量化。我们的方法取得了令人满意的性能(NVH丰度),因为通过人工计数和系统自动计数的比较,我们能够提供令人鼓舞的结果,检测率为78.38%。这项工作的主要贡献是开发和部署一个名为U3S的自动识别系统,用于藻类生物多样性丰度研究,以协助海洋生物学家识别藻类物种,补充现有的操作员密集程序。
A framework for the automatic identification of algae (Neomeris vanbosseae M.A. Howe):U3S
Neomeris vanbosseae M.A. Howe (NVH) is an algae belonging to the Chlorophyta, which is a very diverse group of algae. Therefore when an algae biologist establishes an abundance assessment for algae biodiversity, the taxonomic identification and quantification could frequently lead to a time intensive procedure which is prone to a counting bias, due to fatigue when processing large pools of data samples repeatedly. To improve the effectiveness, this paper proposed a framework, being an assistive tool, to help marine biologists. The framework consists of (1) pre-processing the image, (2) segmenting region of interest, (3) extracting features (namely four different geometric features), (4) evaluating and combining those features based on the given decision criterions, and (5) the quantification. Our methodology achieved satisfactory performance (NVH abundance) as it's able to provide an encouraging result with 78.38% detection rate yielded by the comparison between manual count and our system automatic count. The major contribution of this work is the development and the deployment of an automatic identification system, named U3S, for biodiversity abundance studies of algae to assist the marine biologist in identifying algae species, complementing the existing operator intensive procedures.