Matching, Archiving and Visualizing Cultural Heritage Artifacts Using Multi-channel Images

Recent advancements in low-cost acquisition technologies have made it more practical to acquire real-world datasets on a large scale. This has lead to a number of computer-based solutions for reassembling, archiving and visualizing cultural heritage artifacts. In this thesis, we combine aspects of these technologies in novel ways and introduce algorithms to improve upon their overall efficiency and robustness. First, we introduce a 2-D acquisition system to address the challenge of acquiring higher resolution color and normal maps for large datasets than those available with 3-D scanning devices. Next, we incorporate our normal maps into a novel multi-cue matching system for reassembling small fragments of artifacts. We then present a non-photorealistic rendering pipeline for illustrating geometrically complex objects using images with multiple channels of information. State-of-the-art 3-D acquisition systems capture 3-D geometry at archeological sites using affordable, off-the-shelf scanners. Although multiple scans at varying viewpoints are required to assemble a complete model, robust registration and alignment algorithms, as well as new work-flow methodologies, significantly reduce the post-processing time. However, the color and normal maps obtained from these systems lack the subtle sub-millimeter details necessary for careful analysis, and high fidelity documentation. We introduce an algorithm that generates higher resolution normal maps and diffuse reflectance (true color texture), while minimizing acquisition time. Using shape from shading, we compute our normal maps from high resolution color scans of the object taken at four orientations on a 2-D flatbed scanner. A key contribution of our work is a novel calibration process to measure the observed brightness as a function of the surface normal. This calibration is important because the scanner’s light is linear (rather than a point), and we cannot solve for the surface normal using the traditional formulation of the Lambertian lighting law. High resolution digital SLR cameras provide alternative solutions when objects are too large or fragile to place on a scanner. However, they require more control over the ambient light in the environment and additional manual effort to continually re-position a hand-held flash.