Accuracy Assessment and Classification of Surface Contaminants of Stone Cultural Heritages Using Hyperspectral Image - Focusing on Stone Buddhas in Four Directions at Gulbulsa Temple Site, Gyeongju -

Abstract

Considering the difficulties associated with the creation of deterioration maps for stone cultural heritages, quantitative determination of chemical and biological contaminants in them is still challenging. Hyperspectral image analysis has been proposed to overcome this drawback. In this study, hyperspectral imaging was performed on Stone Buddhas Temple in Four Directions at Gulbulsa Temple Site(Treasure 121), and several surface contaminants were observed. Based on the color and shape, these chemical and biological contaminants were classified into ten categories. Additionally, a method for establishing each class as a reference image was suggested. Simultaneously, with the help of Spectral Angle Mapper algorithm, two classification methods were used to classify the surface contaminants. Method A focused on the region of interest, while method B involved the application of the spectral library prepared from the image. Comparison of the classified images with the reference image revealed that the accuracies and kappa coefficients of methods A and B were 52.07% and 63.61%, and 0.43 and 0.55, respectively. Additionally, misclassified pixels were distributed in the same contamination series.

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