Abstract: Aiming at the problem of effective information loss and lossy quality detection caused by unclear near infrared hyperspectral feature contour of rice, we proposed a combined model of rice hyperspectral typical feature region extraction algorithm based on energy functional active contour wave under mask. The method compared and optimized the hyperspectral segment information between the morphological region and geometric centroid of target samples, and made a generalization visual discrimination for  four producing areas and three kinds of quality rice. The results of MATLAB experiment show that the recognition accuracy of morphological regions of interest is higher, and the accuracy of generalization prediction set is 94.84% by modeling and comparing the spectral information of typical characteristic regions of different quality rice.  The optimal modeling problem of typical characteristic regions of near infrared hyperspectral rice is optimized, and the rapid nondestructive[JP] quality detection of rice is realized.

Key words: hyperspectral, typical characteristic area, visual discrimination, nondestructive quality detection