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Automatic analysis of artistic paintings using information-based measures
Pattern Recognition ( IF 7.5 ) Pub Date : 2021-02-01 , DOI: 10.1016/j.patcog.2021.107864
Jorge Miguel Silva , Diogo Pratas , Rui Antunes , Sérgio Matos , Armando J. Pinho

The artistic community is increasingly relying on automatic computational analysis for authentication and classification of artistic paintings. In this paper, we identify hidden patterns and relationships present in artistic paintings by analysing their complexity, a measure that quantifies the sum of characteristics of an object. Specifically, we apply Normalized Compression (NC) and the Block Decomposition Method (BDM) to a dataset of 4,266 paintings from 91 authors and examine the potential of these information-based measures as descriptors of artistic paintings. Both measures consistently described the equivalent types of paintings, authors, and artistic movements. Moreover, combining the NC with a measure of the roughness of the paintings creates an efficient stylistic descriptor. Furthermore, by quantifying the local information of each painting, we define a fingerprint that describes critical information regarding the artists’ style, their artistic influences, and shared techniques. More fundamentally, this information describes how each author typically composes and distributes the elements across the canvas and, therefore, how their work is perceived. Finally, we demonstrate that regional complexity and two-point height difference correlation function are useful auxiliary features that improve current methodologies in style and author classification of artistic paintings. The whole study is supported by an extensive website (http://panther.web.ua.pt) for fast author characterization and authentication.



中文翻译:

使用基于信息的措施自动分析艺术画

艺术界越来越依赖于自动计算分析来对艺术作品进行认证和分类。在本文中,我们通过分析艺术绘画的复杂性来识别艺术作品中存在的隐藏模式和关系,这是一种量化对象特征之和的措施。具体来说,我们将归一化压缩(NC)和块分解方法(BDM)应用于来自91位作者的4,266幅画的数据集,并研究了这些基于信息的度量作为艺术画描述符的潜力。两种方法都一致地描述了绘画,作家和艺术运动的同等类型。此外,将NC与绘画粗糙度的度量结合起来可以创建有效的样式描述符。此外,通过量化每幅画的本地信息,我们定义了一个指纹,该指纹描述了有关艺术家的风格,他们的艺术影响力和共享技术的关键信息。从更根本上讲,此信息描述了每个作者通常如何在画布上组成和分布元素,以及因此如何看待他们的作品。最后,我们证明了区域复杂性和两点高度差相关函数是有用的辅助功能,可以改善当前艺术绘画的风格和作者分类方法。整个研究得到一个广泛的网站(http://panther.web.ua.pt)的支持,以进行快速的作者特征和认证。和共享技术。从更根本上讲,此信息描述了每个作者通常如何在画布上组成和分布元素,以及因此如何看待他们的作品。最后,我们证明了区域复杂性和两点高度差相关函数是有用的辅助功能,可以改善当前艺术绘画的风格和作者分类方法。整个研究得到一个广泛的网站(http://panther.web.ua.pt)的支持,以进行快速的作者特征和认证。和共享技术。从根本上讲,此信息描述了每个作者通常如何在画布上组成和分布元素,因此,如何看待他们的作品。最后,我们证明了区域复杂性和两点高度差相关函数是有用的辅助功能,可以改善当前艺术绘画的风格和作者分类方法。整个研究得到一个广泛的网站(http://panther.web.ua.pt)的支持,以进行快速的作者特征和认证。我们证明了区域复杂性和两点高度差相关函数是有用的辅助功能,可以改善当前艺术绘画风格和作者分类的方法。整个研究得到一个广泛的网站(http://panther.web.ua.pt)的支持,以进行快速的作者特征和认证。我们证明了区域复杂性和两点高度差相关函数是有用的辅助功能,可以改善当前艺术绘画风格和作者分类的方法。整个研究得到一个广泛的网站(http://panther.web.ua.pt)的支持,以进行快速的作者特征和认证。

更新日期:2021-02-08
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