A Novel Approach for Weed Type Classification Based on Shape Descriptors and a Fuzzy Decision-Making Method

Sensors

Pedro Javier Herrera¹  José. Dorado² 

[1] Centre for Automation and Robotics, CSIC-UPM, 28500 Madrid, Spain;Institute of Agricultural Sciences, CSIC, 28006 Madrid, Spain

关键词: precision agriculture;    weed species discrimination;    fuzzy decision making strategy;    colour segmentation;    Hu invariant moments;    geometric shape descriptors;   

DOI  :  10.3390/s140815304

来源: mdpi

【 摘 要 】

An important objective in weed management is the discrimination between grasses (monocots) and broad-leaved weeds (dicots), because these two weed groups can be appropriately controlled by specific herbicides. In fact, efficiency is higher if selective treatment is performed for each type of infestation instead of using a broadcast herbicide on the whole surface. This work proposes a strategy where weeds are characterised by a set of shape descriptors (the seven Hu moments and six geometric shape descriptors). Weeds appear in outdoor field images which display real situations obtained from a RGB camera. Thus, images present a mixture of both weed species under varying conditions of lighting. In the presented approach, four decision-making methods were adapted to use the best shape descriptors as attributes and a choice was taken. This proposal establishes a novel methodology with a high success rate in weed species discrimination.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.