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作 者:冯金牛 周强[1] 张静[1] 王莹[2] 罗宏杰[2,3] FENG Jin-niu;ZHOU Qiang;ZHANG Jing;WANG Ying;LUO Hong-jie(School of Electrical and Control Engineering,Shaanxi University of Science&Technology,Xi′an 710021,China;Research Institute of Silicate Cultural Heritage,Shaanxi University of Science&Technology,Xi′an 710021,China;School of Material Science and Engineering,Shanghai University,Shanghai 200444,China)
机构地区:[1]陕西科技大学电气与控制工程学院,陕西西安710021 [2]陕西科技大学硅酸盐质文化遗产研究院,陕西西安710021 [3]上海大学材料科学与工程学院,上海200444
出 处:《陕西科技大学学报》2023年第4期180-187,共8页Journal of Shaanxi University of Science & Technology
基 金:国家重点研发计划项目(2019YFC1520100);陕西省科技厅科技计划项目(2019GY-090)。
摘 要:针对于不同历史时期古陶瓷外观特征挖掘不足的现状,从器型和纹饰两个方向研究提取古代玉壶春瓶外观特征的方法,分别在建立玉壶春瓶轮廓模型的基础上精确提取器型特征,构建蕉叶纹纹饰的局部二值模式(Local Binary Pattern, LBP)和方向梯度直方图(Histogram of Oriented Gradient, HOG)等纹饰特征,并通过器型、纹饰特征的广义回归神经网络(Generalized Regression Neural Network, GRNN)融合模型实现元明清三个时期玉壶春瓶的辨识.实验表明:本方法不仅能够准确提取古陶瓷具有代表性的器型和纹饰特征,发掘其外观随时代演变的一般规律,并且能够利用器型和纹饰特征准确判断玉壶春瓶的朝代,辅助古陶瓷文物的研究和数字化保护工作.In this paper,we study the methods of extracting the appearance features of ancient jade pots and spring vases from two directions,including the accurate extraction of vessel shape features,the construction of LoCal Binary Pattern(LBP)and Histogram of Oriented Gradient(HOG)of banana leaf ornamentation based on the establishment of the contour model of jade pots and spring vases,respectively.The method is based on a generalized regression neural network(GRNN)fusion model for the identification of jade vases from the Yuan,Ming and Qing dynasties.The experiments show that this method is not only able to accurately extract the representative features of ancient ceramics,but also to discover the general pattern of the evolution of their appearance over time,and to accurately determine the dynasty of the jade pot spring vase using the features of the vessel type and decoration,which can assist in the research of ancient ceramic relics.
关 键 词:玉壶春瓶 元明清时期 纹饰特征 器型特征 信息融合 GRNN
分 类 号:TP391.4[自动化与计算机技术—计算机应用技术]
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