{"title":"New method for wall cells detection in Arabidopsis thaliana leaves","authors":"M. Forero, Sammy A. Perdomo, M. Quimbaya","doi":"10.1109/STSIVA.2016.7743348","DOIUrl":null,"url":null,"abstract":"A new image processing method for cell detection in leaves of Arabidopsis thaliana is presented. Using complementary image processing techniques, we introduce a good way to obtain the original cell contour shapes, surpassing the limitations given by factors like noise, stomata, blurred edges, and non-uniform illumination. Preliminary results show this process minimizes considerably the time of cell detection in comparison with the traditional biology methods that include a tedious freehand path, and produces matching percentages of true borders over 80%. Experimental results are shown.","PeriodicalId":373420,"journal":{"name":"2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STSIVA.2016.7743348","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A new image processing method for cell detection in leaves of Arabidopsis thaliana is presented. Using complementary image processing techniques, we introduce a good way to obtain the original cell contour shapes, surpassing the limitations given by factors like noise, stomata, blurred edges, and non-uniform illumination. Preliminary results show this process minimizes considerably the time of cell detection in comparison with the traditional biology methods that include a tedious freehand path, and produces matching percentages of true borders over 80%. Experimental results are shown.