Density Weighted Connectivity of Grass Pixels in image frames for biomass estimation

作者：

Highlights：

• A new concept of DWCGP for automatic estimation of grass biomass.

• An integrated framework based on grass segmentation and orientation detection.

• Low estimation error and high robustness to system parameters.

• Effectiveness in supporting fire-prone road identification.

摘要

•A new concept of DWCGP for automatic estimation of grass biomass.•An integrated framework based on grass segmentation and orientation detection.•Low estimation error and high robustness to system parameters.•Effectiveness in supporting fire-prone road identification.

论文关键词：Image analysis,Roadside data analysis,Grass biomass,Gabor filter,Artificial neural networks

论文评审过程：Received 22 September 2017, Revised 9 January 2018, Accepted 30 January 2018, Available online 6 February 2018, Version of Record 23 February 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.01.055