Automated color clustering for medieval manuscript analysis

Given a color image of a medieval manuscript page, we propose a simple, yet efficient algorithm for automatically estimating the number of its color-based pixel groups, K. We formulate this estimation as a minimization problem, where the objective function assesses the quality of a candidate clustering. Rather than using all the features of the given image, we carefully select a subset of features to perform clustering. The proposed algorithm was extensively evaluated on a dataset of 2198 images (1099 original images and their 1099 variants produced by modifying both spatial and spectral resolutions of the originals) from the Yale´s Institute for the Preservation of Cultural Heritage (IPCH). The experimental results show that it is able to yield satisfactory estimates of K for these test images.