Importance of automatic threshold for image segmentation for accurate measurement of fine roots of woody plants

Abstract

The fine roots are considered the key organs for plant survival, growth and productivity. Measurement of fine roots variables is easily and conveniently achieved by means of digital image. The descriptive variables like root area, surface, total length and diameter distribution may be obtained from the image. Analysis of digital image consists from several steps, each of them represents potential source of the error. In this article we want to evaluate the automatic thresholding and its impact on principal variables obtainable from digital scans of the fine roots. We compare 16 different thresholding methods and compare them with the human processed binary images of roots of cork oak (Quercus suber L.). We found some of the thresholding methods perform significantly better than others in the estimation of total projected area however the length estimation error points out a little different order of accuracy.