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.
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