CAJ | 학술논문

基于Mamdani模糊推理的边缘检测，将多个特征作为整体进行一步推理，但不同特征难以兼顾对模糊边缘的敏感和噪声的抑制，导致算法鲁棒性下降。为此，该文提出了一种基于重要性加权的分步推理算法，根据各特征对边缘敏感和噪声抑制的重要性分步进行模糊推理，并加权每步推理结果作为边缘隶属度。并提出了一种基于面积近似的重心法改进算式，能更好兼顾解模糊的准确性和实时性。实验结果表明了该算法的准确性、鲁棒性和实时性。
기우Mamdani모호추리적변연검측，장다개특정작위정체진행일보추리，단불동특정난이겸고대모호변연적민감화조성적억제，도치산법로봉성하강。위차，해문제출료일충기우중요성가권적분보추리산법，근거각특정대변연민감화조성억제적중요성분보진행모호추리，병가권매보추리결과작위변연대속도。병제출료일충기우면적근사적중심법개진산식，능경호겸고해모호적준학성화실시성。실험결과표명료해산법적준학성、로봉성화실시성。
Edge detection based on Mamdani fuzzy inference regards all features as a whole to carry on one-step inference. However, this will decrease the robustness of algorithm since different features are difficult to guarantee both the sensibility for fuzzy edge and the suppression for noise. This paper presents a step-by-step processing scheme based on multi-features importance-weighted fuzzy inference. According to the importance degree of each feature in the edge representation and noise suppression, the proposed method carries on a step-by-step fuzzy inference and weights all inference results to obtain the edge membership. In addition, this paper presents an improved centroid method based on area approximation, which has higher precision and real-time in defuzzification. The experiment results show the precision, robustness and real-time of the proposed algorithm.