SegRoot


Zhejiang University & Purdue University

Overview

Measured variables length
Operating system windows, mac, linux
Licence open-source, freeware
Automation level automated
Plant requirements any
Export formats csv
Other information

Scientific article(s)

SegRoot: A high throughput segmentation method for root image analysis
Tao Wang, Mina Rostamza, Zhihang Song, Liangju Wang, G. McNickle, Anjali S. Iyer-Pascuzzi, Zhengjun Qiu, Jian Jin
Computers and Electronics in Agriculture, 2019 View paper

Description

SegRoot is a fully automated method based on convolutional neural networks, adapted for segmenting root from complex soil background. Our method eliminates the need for delicate feature designing which requires significant expert knowledge. The trained SegRoot networks learned morphological features with different abstraction levels directly from root images. Thus, the generalization and adaptation of the proposed method was expected across different root images.


Source: SegRoot paper

Share your experience

blog comments powered by Disqus