Identification of drawing tools by classification of textural and boundary features of strokes
Recent developments in computer vision provide powerful tools for the examination and classification of data of our cultural heritage. It is generally recognized that the cultural heritage we are preserving for future generations will profit considerably from passing over to state of the art technologies. New camera hardware allows new insights into cultural heritage, especially if infrared cameras are concerned, since they allow the study of structures that are visually hidden. In this paper a strategy for the analysis of underdrawing strokes in infrared reflectograms is presented. Underdrawings are the basic concept or primal sketch of the artist before the complete painting is created. We focus on infrared reflectograms of medieval panel paintings, since their underdrawings are common and help art historians to study the school of the old masters. The purpose of the stroke analysis is the determination of the drawing tool used to draft the painting. This information allows significant support for a systematic stylistic approach in the analysis of paintings. Stroke segmentation in paintings is related to the extraction and recognition of handwriting, therefore similar techniques to segment the strokes from the background incorporating boundary information are used. Following the segmentation of single strokes, a classification of strokes with respect to the drawing tool used to create the strokes is performed. Two different classification methods, one texture-based and one based on active contour models are combined in order to improve the classification results, which are presented and discussed for strokes on selected test panels.
classification underdrawings panel paintings stroke analysis textural features geometric features