摘要
This paper aims to provide a quantitative method that employs image processing in the assessment of surface roughness based on digital photograph field surveys, as in previous studies employing the outdoor integrated digital photography and image processing (O-IDIP) method. Digital photographs were taken on two different days under contrasting outdoor lighting conditions (overcast versus clear sky). Images were captured mounted on a tripod close up to the surface of a 380-year-old wall located at the University of Oxford Botanic Garden in the City of Oxford, UK. Sampling points were established at regular intervals along the border wall and encompassed sections facing west, north, and east, respectively along the survey. Two photographs were taken with a digital camera at each sampling point, one containing a color chart used to calibrate outdoor lighting conditions across images, which was excluded from the other photographic pair. Histogram-based quantification was performed based on images converted to Lab Color mode. The 10-step calibration procedure presented in this paper required more adjustments of contrast. However, more adjustments were not required under a clear sky. Std Dev L measurements were used to establish categories in a simple 3-point roughness index, namely the surface roughness index (SRI). The results denote that pitting did not affect surface roughness measurements. The study shows that it is possible to use Std Dev L measurements to quantify surface roughness on a comparative basis.
This paper aims to provide a quantitative method that employs image processing in the assessment of surface roughness based on digital photograph field surveys, as in previous studies employing the outdoor integrated digital photography and image processing (O-IDIP) method. Digital photographs were taken on two different days under contrasting outdoor lighting conditions (overcast versus clear sky). Images were captured mounted on a tripod close up to the surface of a 380-year-old wall located at the University of Oxford Botanic Garden in the City of Oxford, UK. Sampling points were established at regular intervals along the border wall and encompassed sections facing west, north, and east, respectively along the survey. Two photographs were taken with a digital camera at each sampling point, one containing a color chart used to calibrate outdoor lighting conditions across images, which was excluded from the other photographic pair. Histogram-based quantification was performed based on images converted to Lab Color mode. The 10-step calibration procedure presented in this paper required more adjustments of contrast. However, more adjustments were not required under a clear sky. Std Dev L measurements were used to establish categories in a simple 3-point roughness index, namely the surface roughness index (SRI). The results denote that pitting did not affect surface roughness measurements. The study shows that it is possible to use Std Dev L measurements to quantify surface roughness on a comparative basis.
