Automatic analysis of artistic paintings using information-based measures

التفاصيل البيبلوغرافية
العنوان: Automatic analysis of artistic paintings using information-based measures
المؤلفون: Silva, Jorge Miguel, Pratas, Diogo, Antunes, Rui, Matos, Sérgio, Pinho, Armando J.
المصدر: Pattern Recognition (2021) 107864
سنة النشر: 2021
المجموعة: Computer Science
Mathematics
مصطلحات موضوعية: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Information Theory, Computer Science - Machine Learning
الوصف: 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.
Comment: Website: http://panther.web.ua.pt 24 Pages; 19 pages article; 5 pages supplementary material
نوع الوثيقة: Working Paper
DOI: 10.1016/j.patcog.2021.107864
URL الوصول: http://arxiv.org/abs/2102.01767
رقم الأكسشن: edsarx.2102.01767
قاعدة البيانات: arXiv
الوصف
DOI:10.1016/j.patcog.2021.107864