A near infrared spectral feature extraction method based on functional principal component analysis, and an extraction system thereof. The extraction method comprises steps of: S1, acquiring near infrared spectrum data in multiple samples; S2, preprocessing the near infrared spectrum data using standard normal transformation; S3, obtaining a spline function of the processed near infrared spectrum data; S4, centralizing the spline function; S5, calculating the covariance of the centralized spline function in different waveband functions; S6, calculating the j-th feature value of the covariance; S7, calculating cumulative contribution; and S8, calculating scores of functional principal components in equations of different wavebands.
NEAR INFRARED SPECTRAL FEATURE EXTRACTION METHOD AND SYSTEM BASED ON FUNCTIONAL PRINCIPAL COMPONENT ANALYSIS