The complex and changeable structures of ancient Chinese characters result in the decreasing accuracy of their image retrieval. To resolve this problem, a new retrieval method based on dual hesitant fuzzy sets is proposed. Dual hesitation fuzzy sets that can express uncertain information more comprehensively are employed in the feature extraction process of directional line elements. The multiattribute evaluation index of adjacent grids for the current grid and its corresponding membership and nonmembership functions are established, and the weight of each attribute is calculated by the dual hesitation fuzzy entropy, such that the proposed features can fully reflect the topological structure of ancient Chinese characters. Using the dual hesitation fuzzy correlation coefficient to measure the similarity between the ancient Chinese character images to be retrieved and the candidate images, the retrieval of ancient Chinese character images is realized. Experiments show that when the t0hreshold value of the correlation coefficient is 0.9, the average retrieval accuracy is 90.4%.

中文翻译：

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基于双重犹豫模糊集的古代汉字图像检索

古代汉字结构复杂多变，导致其图像检索精度下降。为了解决这个问题，提出了一种基于双重犹豫模糊集的检索方法。在方向线元特征提取过程中，采用了可以更加全面地表达不确定信息的双重犹豫模糊集。建立了当前网格的相邻网格的多属性评价指标及其对应的隶属度和非隶属度函数，并通过对偶犹豫模糊熵计算了每个属性的权重，使得所提出的特征能够充分反映出古代汉语的拓扑结构。人物。利用双重犹豫模糊相关系数测量待检索的古代汉字图像与候选图像之间的相似度，实现了古代汉字图像的检索。实验表明，当相关系数的t0hreshold值为0.9时，平均检索准确率为90.4％。