Zhang Wenli, Tian Fengchun, Song An, Hu Youwen
College of Communication Engineering, Chongqing University, 174 Sha Pingba, Chongqing 400044, China.
Sensors (Basel). 2018 Apr 13;18(4):1188. doi: 10.3390/s18041188.
Light absorption gas sensing technology has the characteristics of massive parallelism, cross-sensitivity and extensive responsiveness, which make it suitable for the sensing task of an electronic nose (e-nose). With the performance of hyperspectral resolution, spatial heterodyne spectrometer (SHS) can present absorption spectra of the gas in the form of a two dimensional (2D) interferogram which facilitates the analysis of gases with mature image processing techniques. Therefore, a visual e-nose system based on SHS was proposed. Firstly, a theoretical model of the visual e-nose system was constructed and its visual maps were obtained by an experiment. Then the local binary pattern (LBP) and Gray-Level Co-occurrence Matrix (GLCM) were used for feature extraction. Finally, classification algorithms based on distance similarity (Correlation coefficient (CC); Euclidean distance to centroids (EDC)) were chosen to carry on pattern recognition analysis to verify the feasibility of the visual e-nose system.
光吸收气体传感技术具有大规模并行性、交叉敏感性和广泛响应性等特点，使其适用于电子鼻（e-nose）的传感任务。空间外差光谱仪（SHS）具有高光谱分辨率的性能，能够以二维（2D）干涉图的形式呈现气体的吸收光谱，便于利用成熟的图像处理技术对气体进行分析。因此，提出了一种基于SHS的可视化电子鼻系统。首先，构建了可视化电子鼻系统的理论模型，并通过实验获得了其可视化图谱。然后，使用局部二值模式（LBP）和灰度共生矩阵（GLCM）进行特征提取。最后，选择基于距离相似度的分类算法（相关系数（CC）；到质心的欧几里得距离（EDC））进行模式识别分析，以验证可视化电子鼻系统的可行性。
