Rotation-invariant NCC for 2D color matching of arbitrary shaped fragments of a fresco

•RINCCAS is designed to problems of DAFNE (Digital Anastylosis of Frescos challeNgE).•RINCCAS is based on the classic NCC (Normalized Cross Correlation).•RINCCAS extends NCC to compare color picture fragments of arbitrary curved contours.•The new method inherits the NCC precision adding a rotation invariance to it.•The method 2-d phase gives good recognition of spurious in the fragments for a fresco. The proposed RINCCAS method, an abbreviation of the paper title, was originally developed to participate in DAFNE (Digital Anastylosis of Frescos challeNgE) race, June-July 2019. The method consists of two phases. Phase 1 extends the classic Normalized Cross Correlation (NCC) for template matching of arbitrary curvilinear 2D shapes of fragments that are assumed belonging to a fresco as perceived in a photograph. For this purpose, each fragment is approximated by one (up to several, but not overlapping) Maximal & Axes-Collinear Inner Rectangles (MACIRs). The extension also includes rotation invariance and vector compatibility of NCC in respect to the three (RGB) color channels. The high positioning accuracy makes it possible to identify eventual/existing spurious fragments in Phase 2 of RINCCAS, as follows − by HSV scheme for color differences, and by accurate recognition of overlaps among the fragments. The first phase is ‘log-cubically’ complex in speed, estimated on the average size of the MACIRs of the fragments. For some DAFNE tasks, the 1st phase of RINCCAS requires high computational resources (HPC), while a conventional PC is sufficient for its 2nd phase, even in the case of multiple interactive optimization of the ratio between true and spurious fragments. Graphical abstract [Display omitted]