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Title: In Situ Height and Width Estimation of Sorghum Plants from 2.5d Infrared Images

Plant phenotyping, or the measurement of plant traits such as stem width and plant height, is a critical step in the development and evaluation of higher yield biofuel crops. Phenotyping allows biologists to quantitatively estimate the biomass of plant varieties and therefore their potential for biofuel production. Manual phenotyping is costly, time-consuming, and errorprone, requiring a person to walk through the fields measuring individual plants with a tape measure and notebook. In this work we describe an alternative system consisting of an autonomous robot equipped with two infrared cameras that travels through fields, collecting 2.5D image data of sorghum plants. We develop novel image processing based algorithms to estimate plant height and stem width from the image data. Our proposed method has the advantage of working in situ using images of plants from only one side. This allows phenotypic data to be collected nondestructively throughout the growing cycle, providing biologists with valuable information on crop growth patterns. Our approach first estimates plant heights and stem widths from individual frames. It then uses tracking algorithms to refine these estimates across frames and avoid double counting the same plant in multiple frames. The result is a histogram of stem widths and plantmore » heights for each plot of a particular genetically engineered sorghum variety. In-field testing and comparison with human collected ground truth data demonstrates that our system achieves 13% average absolute error for stem width estimation and 15% average absolute error for plant height estimation.« less
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  1. Univ. of California, Berkeley, CA (United States)
Publication Date:
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Electronic Imaging
Additional Journal Information:
Journal Volume: 2017; Journal Issue: 17; Journal ID: ISSN 2470-1173
Research Org:
University of Illinois at Urbana-Champaign, IL (United States)
Sponsoring Org:
USDOE Advanced Research Projects Agency - Energy (ARPA-E)
Country of Publication:
United States
09 BIOMASS FUELS; 97 MATHEMATICS AND COMPUTING; Biofuel; Computer vision; Image processing; Phenotyping; Stereoscopy
OSTI Identifier: