Large scale style based dating of medieval manuscripts

In this paper we propose a novel approach for manuscript dating based on shape statistics. Our goal was to develop a strategy well suited for a large scale dating effort where heterogeneous collections of thousands of manuscripts could be automatically processed. The proposed method takes the gray scale image as input, then uses the stroke width transform and a statistical model of the gradient image to find ink boundaries. Finally, a distribution over common shapes, quantified using shape context descriptors, is produced for each manuscript image. The proposed method is binarization-free, rotational invariant and requires minimal segmentation. We evaluate our work on the 10000+ manuscripts collection \"Svenskt diplomatariums huvudkartotek\", consisting of charters from the medieval period of todays Sweden. The images, originally intended for web viewing, were of low quality and had compression artifacts. Due to unsupervised feature learning and regression, the collection could be dated with a median absolute error below 19 years even though we only used 5% of the labels in the estimator training.