A local extrema based method on 2D brightness temperature maps for detection of archaeological artifacts

Archaeological studies using computer vision based analysis methods on thermal imageries mainly lack an important stage of pointwise detection of artifact positions, which is needed for the automation of the system in a generic application. In this paper, we propose a pointwise detection method working in the thermal range of hyperspectral band for archaeological artifacts. The proposed method first optimally converts a given 3D hyperspectral image of the searched scene into a 2D brightness-temperature map by minimizing the mean square error (MSE) between the spectral radiance of a pixel and the Planck curves generated at different temperatures. The local maxima and minima are then found on the resulting 2D map as the candidate points. Finally, a score assignment is performed on the candidate points by using their temperature difference with respect to their neighborhood. The results on the thermal images taken from a test scene have indicated a good correlation between the extrema points and artifact positions.