基于图像的作物病害状态表观三维模拟方法  

Three dimensional visual simulation method of crop disease state based on image

作　　者：苗腾[1,2,3,4] 郭新宇 温维亮[1,3,4] 肖伯祥[1,3,4] 陆声链[1,3,4] 

机构地区：[1]北京农业信息技术研究中心,北京100097 [2]沈阳农业大学信息与电气工程学院,沈阳110866 [3]国家农业信息化工程技术研究中心,北京100097 [4]数字植物北京市重点实验室,北京100097

出　　处：《农业工程学报》2016年第7期181-186,共6页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家863计划课题(2012AA101906);国家自然科学基金(31171454);北京市科技计划项目(D151100004215004);北京市自然科学基金(4162028);国家自然科学基金(31501217);北京市农林科学院博士后基金项目支持

摘　　要：为了解决病害表观信息难以获取导致的作物病害状态三维模拟困难的问题,该文提出一种基于图像的作物病害状态表观模拟方法。该方法首先利用单张图像提取病斑的形状、颜色以及位置特征,并对其变化过程进行自动推断;基于这些特征信息,对病害的病状以及病症表观进行建模。试验结果表明,该方法可以利用网络中已有的病斑图像对病害侵染导致的作物表观变化进行真实地三维模拟,一定程度上解决病害表观信息缺失的问题,为数字农业设计及农业科普培训动画的制作提供有力工具。Simulation of three-dimensional (3D) crop scene infected by crop disease is a tough task, because the related appearance data information is difficult to obtain. To obtain specific disease appearance information, careful bacteria culture and continuous observation may be needed with long-time experimental work and precise environmental control. This paper presents a general method to simulate the appearance transition of crop leaves infected by common diseases based on existing image in the Internet. We assume that a disease image contains some key appearance information in the process of disease infection. Based on this assumption, a set of static properties are extracted from image including shape and color of disease spots on the crop surface, and meanwhile the relevant dynamic transition processes of these properties are also deduced. For analyzing color transition, K-MEANS is firstly used to classify the color vectors of pixels in disease image into 8 categories and the average color vector of each category is computed which is called disease color feature vector. Then, these 8 vectors are sorted based on their proportions of green channel. To get a continual color aging simulation result, 7 linear functions are generated by interpolation between adjacent vectors. Finally, 141 discrete color vectors are sampled from these functions and used to generate the disease color transition texture. In order to obtain dynamic morphogenesis process of disease spot, the threshold segmentation method is firstly applied to segment the disease spot pixels from the pixels of normal crop leaves. Then a gray value is computed for each disease spot pixel based on the mimimum Euclidean distance between pixel's color vector and each disease color feature vector. These gray values of each disease spot pixel are recorded into the texture called morphogenesis texture. The distribution of disease spot on the crop organ surface is complex and random. A interactive interface tool has been developed for designing the distribution. With

关 键 词：作物 病害 模型 虫害控制 三维 数字植物 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] S126[自动化与计算机技术—计算机科学与技术] S43[农业科学—农业基础科学]