An automated, high-throughput method for standardizing image color profiles to improve image-based plant phenotyping.

ABSTRACT: High-throughput phenotyping has emerged as a powerful method for studying plant biology. Large image-based datasets are generated and analyzed with automated image analysis pipelines. A major challenge associated with these analyses is variation in image quality that can inadvertently bias results. Images are made up of tuples of data called pixels, which consist of R, G, and B values, arranged in a grid. Many factors, for example image brightness, can influence the quality of the image that is captured. These factors alter the values of the pixels within images and consequently can bias the data and downstream analyses. Here, we provide an automated method to adjust an image-based dataset so that brightness, contrast, and color profile is standardized. The correction method is a collectio

SUBMITTER: Berry JC 

PROVIDER: S-EPMC6174877 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature