Data normalization of leaf color based on fuzzy comprehensive evaluation for visualization model

In order to improve the accuracy of data which was used in producing the model of leaf color in the process of visualization, taking the data of leaf color from maize as a research object, an evaluation system on the accuracy of chlorophyll data was created with the method of fussy comprehensive evaluation. Meanwhile, data of leaf color in different standard were translated and checked in this paper. The results showed that the absolute error between chlorophyll value translated from SPAD which was measured with the index of fuzzy comprehensive evaluation and the value translated from RGB was less than 0.111 mg/g, the accuracy degree of measured leaf-color model data was proved to reach level 2 which also represented exactness. The accuracy of chlorophyll data measure method under the evaluation system can meet the requirement for normalization of data acquisition of leaf color in the process of visualization.