Classification of mineral inclusions in ancient ceramics: comparing different modal analysis strategies

Digital image analysis has recently emerged as a powerful tool for the analysis of the ceramic thin sections. By producing quantitative data, it increases the usefulness of ceramic petrography to address archeological questions. Despite several works considering digital image analysis to study archeological ceramic materials, so far, no work has been proposed to evaluate the possibilities of optical microscopy (OM) image analysis for classification and modal analysis, knowing its advantages and drawbacks, as compared to scanning electron microscopy (SEM) image processing. In this work, we propose an algorithm to count the mineral inclusions correctly classified by OM image analysis with respect to SEM images. The proposed algorithm is based on a matching mechanism applied to the regions of interest (ROIs) detected in the OM images according to the corresponding ROIs as detected in the SEM images. Moreover, a comparison with point counting on the same OM images is also provided to evaluate the pros and cons of each method. Two Late Acacus (Mesolithic) potsherds (8900–4200 BP) are considered as case study for modal analysis to identify and classify quartz, feldspars, and carbonate aggregates as mineral inclusions.