基于深度学习的景观植物颜色特征提取方法  

Method for Extracting Color Characteristics of Landscape Plants Based on Deep Learning

作　　者：林开颜[1] 牛程远 张浩平 杨学军[1] LIN Kai-yan;NIU Cheng-yuan;ZHANG Hao-ping;YANG Xue-jun(Modern Agricultural Science and Engineering Institute,Tongji University,Shanghai 200092,China)

机构地区：[1]同济大学现代农业科学与工程研究院,上海200092

出　　处：《科学技术与工程》2024年第17期7059-7065,共7页Science Technology and Engineering

基　　金：上海市科委科技创新行动计划课题(23N21900400)。

摘　　要：景观植物的颜色特征及其变化规律可以为植物景观季相分析和设计提供科学依据,但传统的色彩量化分析工作量大且获得的色彩特征准确度低,分析结果易受主观因素影响。针对以上问题,基于UNet++深度学习网络框架,提出一种改进的图像分割模型:在UNet++网络中添加了嵌有注意力机制模块和空洞卷积的全新编码器以增强对植株细节信息的捕捉。提取分割后植株图像在各颜色空间的色彩特征分量,利用Relief算法对12种颜色特征进行筛选。在建立的景观植株数据集上验证改进模型的有效性,实验结果表明:改进模型分割结果的准确率为97.8%,经过筛选分析得到Lab颜色空间内的a通道特征可以作为衡量景观植株随季节变化最有区分度的颜色指标。改进后的模型和特征筛选方法可以为景观植株的季相变化研究和农业作物的特征获取提供技术支撑。The color characteristics and their variation rules of landscape plants are used as scientific basis for the seasonal analysis and design of landscape plants.However,with the disadvantages of heavy workload and low accuracy,the traditional quantitative analysis results are easily affected by subjective factors.In order to solve the problems above,based on deep learning network framework of UNet++,an improved image segmentation model was proposed,adding a new encoder embedded with an attention module and dilated convolution to the UNet++ network so as to enhance the capture of detail plant information.After extracting the color feature components of the segmented plant images,the Relief algorithm was used to filter these 12 color features.The effectiveness of the improved model was verified on the established landscape plant dataset.The experimental results show that the accuracy of the segmentation results is 97.8%,and the ‘a' channel feature in the Lab color space can be used as the most discriminative color index to measure the seasonal changes of landscape plants.The improved model and the feature selection method can provide technical support for the research of the seasonal changes of landscape plants and the acquisition of the characteristics of agricultural crops.

关 键 词：图像分割 景观植物 深度学习 特征选择 

分 类 号：S126[农业科学—农业基础科学] S43