To establish a method based on near-infrared(NIR) hyperspectral imaging technology which could identify red ginseng from different origins by fusing NIR spectra and image texture features.Methods:The near-infrared hyperspectral data of red ginseng ROI were extracted to be further de-noised by various pre-processing algorithm.Texture features are extracted from images using gray co-occurrence matrix(GLCM) and gray run matrix(GLRLM)，and near-infrared spectroscopy and image data are fused.Partial least squares discriminant analysis(PLS-DA) and support vector machine classification(SVC) were used here to establish the origin classification model.Results:The model constructed by full-band spectral combined with GLRLM gained the best performance，with accuracy of 90.0% and 91.2%，respectively.The model was further evaluated using confusion matrix and ROC curves.The SVC model performed better in the confusion matrix，with the classification accuracy of 100%，91% and 83% for red ginseng from Jilin，Heilongjiang and Liaoning.According to ROC characteristic curve evaluation，the areas under the optimal curve of the two models are 0.97 and 0.96，respectively.Conclusion:This research provides a new method for rapid identification of red ginseng from different origins.