{"title":"Fynbos leaf online plant recognition application","authors":"S. Winberg, S. Katz, A. Mishra","doi":"10.1109/NCVPRIPG.2013.6776220","DOIUrl":null,"url":null,"abstract":"Computer-aided plant identification combines computer vision and pattern recognition. The Cape Floristic Kingdom is the most varied of plant kingdoms, comprising thousands of species of fynbos plants. While it is easier to classify fynbos when they are flowering, mostly flower for only a few weeks in a year. This paper concerns an image processing application for automatic identification of certain fynbos using leaf photographs. The architecture of this application is overviewed prior to focusing on the leaf recognition operations, and how these were experimentally tested using a series of experiments, culminating in a comprehensive test to measure identification accuracy, effectiveness of the online user interface, and the processing speed. Our conclusions reflect on the overall effectiveness of the application and our plans to take it further.","PeriodicalId":436402,"journal":{"name":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCVPRIPG.2013.6776220","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Computer-aided plant identification combines computer vision and pattern recognition. The Cape Floristic Kingdom is the most varied of plant kingdoms, comprising thousands of species of fynbos plants. While it is easier to classify fynbos when they are flowering, mostly flower for only a few weeks in a year. This paper concerns an image processing application for automatic identification of certain fynbos using leaf photographs. The architecture of this application is overviewed prior to focusing on the leaf recognition operations, and how these were experimentally tested using a series of experiments, culminating in a comprehensive test to measure identification accuracy, effectiveness of the online user interface, and the processing speed. Our conclusions reflect on the overall effectiveness of the application and our plans to take it further.