青岛市大气颗粒物SEM图像数据集

A dataset of SEM images of atmospheric particles in Qingdao

本文选取青岛市7个具有代表性的采样点,分时段进行大气颗粒物样本的采集,然后通过扫描电镜,进一步得到颗粒物的SEM(Scanning Electron Microscope)图像。通过对得到SEM图像的形貌特征进行观察分析,进而挑选出含有形貌特征明显的颗粒物的SEM图像,共计334张图片。基于得到的大气颗粒物的SEM图像进行分析研究,根据其形貌特性的不同将颗粒物分为7类:链条状颗粒物、絮状颗粒物、纤维状颗粒物、球状颗粒物、类球状颗粒物、不规则矿物颗粒物、规则矿物颗粒物。将得到的SEM图片采用水平翻转、色彩平衡、亮度变换、模糊处理等相应的图像处理方法进行颗粒物SEM图像样本的扩展,生成新的图片样本,并将其添加到数据集中。从而建立起含有7类大气颗粒的SEM图像数据集,共含有2672张SEM图片。本文所建立的数据集可以用于采用机器学习等相关方法对大气颗粒物进行识别分类、分割等相关研究,也可为大气颗粒物相关研究提供基础数据资料。

In this paper,we selected seven representative sampling points in Qingdao to collect atmospheric particulate samples in different periods,and then obtained the SEM(Scanning Electron Microscope)images of particulate matters through scanning electron microscopy.By observing and analyzing the morphological characteristics of the images,we identified and selected 334 SEM images of particles with distinct morphological characteristics.Based on the obtained SEM images of atmospheric particles,the particles are divided into seven categories according to their morphological characteristics:chain particles,flocculent particles,fibrous particles,spherical particles,quasi spherical particles,irregular mineral particles,and regular mineral particles.These obtained SEM images are further enhanced using corresponding image processing methods such as horizontal inversion,color balance,brightness transformation,fuzzy processing,etc.New image samples are generated and added to the dataset,presenting a dataset of SEM images for seven types of atmospheric particles,totaling 2,672 SEM images in total.The dataset can be used for identifying,classifying,segmenting research on atmospheric particles using machine learning and other related methods.Moreover,it can provide fundamental data for other related research on atmospheric particles.