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Model Based Approach for Identification of Relevant Images from Ancient Paintings

机译:基于模型的古代绘画相关图像识别方法

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In this paper an attempt is made to retrieve the relevant paintings based on the approach of the artist using Generalized Bivariate Laplacian Mixture Model (GBLMM). This article helps in understanding the outline of assorted artists and help as a means to categorize a scrupulous painting based on the style or the text ingrained within the images. To profile the artist style GBLMM is used. The projected model helps to discriminate the strokes of the artists and lend a hand in the classification of paintings. The proposed model is implemented using high resolution Chinese painting images.
机译:本文尝试使用广义双变量拉普拉斯混合模型(GBLMM),根据画家的方法来检索相关绘画。本文有助于理解各种艺术家的轮廓,并有助于根据图像中根深蒂固的风格或文字对一幅细密的绘画进行分类。要分析艺术家风格,请使用GBLMM。投影模型有助于区分艺术家的笔画,并有助于绘画的分类。所提出的模型是使用高分辨率的中国画图像实现的。

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