Crop and weed discrimination using Laws’ texture masks

作     者：Radhika Kamath Mamatha Balachandra Srikanth Prabhu 

作者机构：Department of Computer Science and EngineeringManipal Institute of TechnologyManipal Academy of Higher EducationManipalIndia 

出 版 物：《International Journal of Agricultural and Biological Engineering》 (国际农业与生物工程学报（英文）)

年 卷 期：2020年第13卷第1期

页      面：191-197页

核心收录：

学科分类：08[工学] 080502[工学-材料学] 0805[工学-材料科学与工程（可授工学、理学学位）] 

主　　题：precision agriculture crop weed texture analysis classifier 

摘      要：Computers have become an integral part of human *** are used in almost every field even in *** like computer vision-based pattern recognition are being used to detect diseases and pests like weeds affecting the *** Weeds are unwanted plants growing among crops competing for nutrients,water,and *** can significantly reduce the quality and yield of the crops incurring a huge loss to the *** paper investigates the use of texture features extracted from Laws’texture masks for discrimination of Carrot crops and weeds in digital ***’texture method is one of the popular methods used to extract texture features in medical image processing,though not much explored in plant-based images or agricultural *** experiment was carried out on two categories of benchmark digital image datasets of Carrot crop and Carrot weed respectively,which are publicly available.A total of 70 texture features were *** dimensionality reduction technique was used to get the optimal *** features were then used to train the Random Forest *** results and observations from the experiment showed that the classifier achieved above 94%accuracy.