The feasibility of the application of image/signal processing for measuring, marking, matching, and sorting vast quantities of data derived from materials typically found in artworks is presented through four case studies. Different patterns produced by canvas weave structures, surface textures of historic photographic papers, chain line intervals in Rembrandt’s printing papers, and watermark variations have been subjected to different modes of computational analysis. The art-historical implications that result from computer-generated algorithms – including dating, attribution, authenticity, and workshop practices – can be considered as “computational connoisseurship.” The case studies discussed point to future areas for research. Finally, because of the need for statistically meaningful datasets of images, a practical means of recording internal paper structure is introduced.

中文翻译：

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计算鉴赏：使用自动图像分析增强检查

通过四个案例研究展示了应用图像/信号处理来测量、标记、匹配和分类源自艺术品中常见材料的大量数据的可行性。由帆布编织结构产生的不同图案、历史相纸的表面纹理、伦勃朗印刷纸中的点划线间隔以及水印变化都经过了不同的计算分析模式。由计算机生成的算法产生的艺术史影响——包括约会、归属、真实性和工作坊实践——可以被视为“计算鉴赏力”。讨论的案例研究指出了未来的研究领域。最后，由于需要具有统计意义的图像数据集，