Identification of various food residuals on denim based on hyperspectral imaging system and combination optimal strategy  

作　　者：Yuzhen Chen Ziyi Xu Wencheng Tang Menghan Hu Douning Tang Guangtao Zhai Qingli Li 

机构地区：[1]Shanghai Key Laboratory of Multidimensional Information Processing,School of Communication&Electronic Engineering,East China Normal University,Shanghai 200062,China [2]School of Statistics,East China Normal University,Shanghai 200062,China [3]Institute of Image Communication and Information Processing,Shanghai Jiao Tong University,Shanghai 200240,China [4]McCormick School of Engineering,Northwestern University,Evanston,IL,United States

出　　处：《Artificial Intelligence in Agriculture》2021年第1期125-132,共8页农业人工智能（英文）

基　　金：sponsored by the National Natural Science Foundation of China(No.61901172,No.61831015,No.U1908210);the Shanghai Sailing Program(No.19YF1414100);the“Chenguang Program”supported by Shanghai Education Development Foundation and Shanghai Municipal Education Commission(No.19CG27);the Science and Technology Commission of Shanghai Municipality(No.19511120100,No.18DZ2270700,No.18DZ2270800);the foundation of Key Laboratory of Artificial Intelligence,Ministry of Education(No.AI2019002);and the Fundamental Research Funds for the Central Universities.

摘　　要：As the science and technology develop,crime methods and scenes have become increasingly complex and diverse.Trace evidence analysis has become amore and more important criminal investigation technology and liquid is the main form of trace evidence.Food can provide not only energy,but clues to solve crimes.In this study,we build a hyperspectral imaging system to detect liquid residue traces,including apple juice,coffee,cola,milk and tea,on denims with light,middle and dark colors.The obtained hyperspectral images are first subjected to spectral calibration and hyperspectral data pretreatment.Subsequently,Partial Least Squares(PLS)is applied to select the informative wavelengths from the preprocessed spectra.For modeling phase,the combination optimal strategy,support vector machine(SVM)combined with random forest(RF),is developed to establish classification models.The experimental results demonstrate that the combination optimal model can achieve TPR,FPR,Precision,Recall,F1,and AUC of 83.5%,2.30%,79.7%,83.5%,81.6%,and 94.7%for classifying fabrics contaminated by various food residuals.With respect to the classification of liquid and fabric types,the combination optimalmodel also yields satisfactory classification performance.In future work,wewill expand the types of liquid,and make appropriate adjustment to algorithms for improving the robustness of classification models.This research may play a positive role in the construction of a harmonious society.

关 键 词：Hyperspectral imaging Food residual on denim Combination optimal strategy Variable selection Forensic application 

分 类 号：TG1[金属学及工艺—金属学]