title: Easy Leaf Area: Automated digital image analysis for rapid and accurate measurement of leaf area.
abstract: OBJECTIVE
  Measurement of leaf areas from digital photographs has traditionally required significant user input unless backgrounds are carefully masked. Easy Leaf Area was developed to batch process hundreds of Arabidopsis rosette images in minutes, removing background artifacts and saving results to a spreadsheet-ready CSV file. •
  
  
  RESULTS
  Easy Leaf Area uses the color ratios of each pixel to distinguish leaves and calibration areas from their background and compares leaf pixel counts to a red calibration area to eliminate the need for camera distance calculations or manual ruler scale measurement that other software methods typically require. Leaf areas estimated by this software from images taken with a camera phone were more accurate than ImageJ estimates from flatbed scanner images. •
  
  
  CONCLUSIONS
  Easy Leaf Area provides an easy-to-use method for rapid measurement of leaf area and nondestructive estimation of canopy area from digital images.
authors.affiliation: Department of Plant Sciences, University of California, One Shields Avenue, Davis, California 95616 USA.
authors.forename: Hsien Ming
authors.initials: HM
authors.lastname: Easlon
authors.affiliation: Department of Plant Sciences, University of California, One Shields Avenue, Davis, California 95616 USA.
authors.forename: Arnold J
authors.initials: AJ
authors.lastname: Bloom
keywords: Arabidopsis; Python; digital images; leaf area