This paper proposes a fuzzy classification system and its application in tobacco leaves grading. The mathematic description of the fuzzy classification model is given out, and we discuss the fuzzy membership function to calculate the membership of the feature of the pattern and how to obtain the confidence of the feature vector. We also discuss the technique to standardize the pattern space and the optimization of the class spaces. And then the fuzzy reasoning technique in the classification system is provided. Finally, we apply this fuzzy classification model in the tobacco leaves grading system (TGS) to show the efficiency, and conduct experiments and comparison with different methods to prove that the TGS have the similar grading ability as a human expert in practice.
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