To achieve spectral characterization of color scanners, a spectral characterization model based on GA-BP and PCA was proposed. Firstly, the dimension of spectral reflectance was reduced by PCA. The GA-BP neural network model was built with input of variables of RGB signal and output of variables of low dimensional spectrum signal. Any low dimensional spectrum signal could be got by this model with any input RGB signal, while the spectral reflectance could be reconstructed by PCA. The spectral characteristics of color scanners were achieved. Experimental results show that the extremum problem of BP neural network could be effectively improved by GA. PCA could improve the operating efficiency of the model under the circumstances of maintaining accuracy. This implied it was a high-precision color scanner characte-ristic model.