ZUO Jia-qian, WANG Hong-qiu, TAN Ling-yu, et al. SVM-based recognition algorithm by Raman spectra for entry-exit special items[J]. 2018, (6): 56-58+65.
ZUO Jia-qian, WANG Hong-qiu, TAN Ling-yu, et al. SVM-based recognition algorithm by Raman spectra for entry-exit special items[J]. 2018, (6): 56-58+65. DOI: 10.13873/j.1000-9787(2018)06-0056-03.
基于SVM的出入境特殊物品拉曼光谱识别方法
摘要
出入境特殊物品的无损快速检测是出入境检验检疫查验工作的难点。介绍了相似性度量识别方法
提出了采用支持向量机(SVM)对出入境特殊物品的拉曼光谱进行分类处理
并对SVM进行针对性改进
将高维向量降维处理
提升物质识别准确度。结果表明:改进SVM有望为出入境特殊物品的无损快速检测提供有效的辅助手段。
Abstract
Fast and nondestructive detection of special items has always been the difficulty in inspection and quarantine. The recognition method of similarity measurement is introduced
and is classified and processed Raman spectra of special items is classified and processed by support vector machine( SVM) is proposed
the SVM is improved for reducing dimension of processing high dimensional vector and enhance the identification accuracy.The results show that the improved SVM is expected to provide an effective auxiliary means for nondestructive and rapid detection for special items in inspection and quarantine system.