Abstract
The use of mobile devices is increasing in the cultural heritage and museum context. The most common approach is to provide a customized mobile device to the museum visitor to navigate museum spaces. In this paper, a mobile cultural heritage guide is presented, which enables image based navigation of rock art sites using computer vision and image processing algorithms for rock art image feature detection and extraction. Traditionally such systems have used algorithms such as Scale-Invariant Feature Transform (SIFT), Speeded-Up Robust Features (SURF) and Oriented Fast and Rotational Brief (ORB). The three algorithms have been integrated in a prototype and their performance has been evaluated. It was observed that digital recognition of rock art images is possible under certain image preprocessing conditions. Also, the evaluation result shows that, generally, SIFT has good accuracy and, when used in conjunction with K Nearest Neighbor, has acceptable matching speed.
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Olojede, A., Suleman, H. (2015). Investigating Image Processing Algorithms for Navigating Cultural Heritage Spaces Using Mobile Devices. In: Allen, R., Hunter, J., Zeng, M. (eds) Digital Libraries: Providing Quality Information. ICADL 2015. Lecture Notes in Computer Science(), vol 9469. Springer, Cham. https://doi.org/10.1007/978-3-319-27974-9_22
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DOI: https://doi.org/10.1007/978-3-319-27974-9_22
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