The invention provides a
textile classification and identification method based on an
infrared spectrum detection technology. The
textile classification and identification method comprises the following steps: S1, firstly, carrying out
moisture absorption on dried samples of different types of textiles; for the same sample, preparing sub-samples with different water contents according to differentmoisture
absorption time; s2, collecting near
infrared spectrums of all the sample sub-samples; s3, performing two-dimensional
correlation spectrum analysis on a series of sub-sample near-
infrared spectra of each sample to obtain a synchronous two-dimensional correlation
spectrogram and an asynchronous two-dimensional correlation
spectrogram, and then fusing the synchronous two-dimensional correlation
spectrogram and the asynchronous two-dimensional correlation spectrogram to obtain a mixed two-dimensional correlation spectrogram; and S4, establishing an image classification model by using aGoogLeNet image recognition model based on a deep
artificial neural network in combination with a transfer learning method according to the spectral images of the different types of samples in the step S3, thereby realizing classification and recognition of the different types of
textile samples. The method can effectively identify and classify different types of textiles with complex components and highly similar compositions.