Measuring Surface Roughness through the Use of Digital Photography and Image Processing

Abstract

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.

New (Digital) Technique for Areal Measurements of Stonewall Surface Roughness

“…It is noteworthy here that the % Mean L and % Median L are strongly positively correlated, with r = 0.95, so that either measure can be used to quantify surface roughness based on histogram-based outputs for the CIE Lab color space. Table 1, which contains a summary of these results, is provided to supplement information already provided by Thornbush (2014b , Table 1). …”

“…In this way, a total of 38 samples were acquired for each profile, for a total (for four profiles) of 152 depth measurements for every block, for a total of 12 sites (out of 18 sites used in the previous study by Thornbush, (2014b), totaling 1,824 measurements. It was not possible to gain access (due to a grown vegetation cover on the walls) to every site included in the previous study and Sites 8-9, 11-12, 14 and 18 had to be omitted.…”

“…Following up on Thornbush (2014b), further research was executed at the University of Oxford Botanic Garden on 15 August 2014. Digital photographs (acquired previously on 24 August 2012) were obtained with a digital camera: FujiFilm Finepix J32 with 12.2 Megapixels (M) with flash off and macro on at 3 M image resolution mounted on a tripod at regular intervals (c. 10 m apart) and at a constant height of 1.5 m above ground level, so that similar wall heights are represented in this field study.…”

“…This method, which calibrated color using a colorchecker, was more recently applied to measure the greening of walls (Thornbush, 2013). Most recently, Thornbush (2014b) used the O-IDIP method in two different days in order to test for the effect of outdoor lighting (overcast versus clear sky). As before, histogram-based quantification was derived from images captured on a tripod set close-up in front of a c. 380-year-old wall at the University of Oxford Botanic Garden.…”

“…The author has shown the usefulness of an integrated (outdoor) digital photography and image processing (O-IDIP) method that considers entire surface areas for color quantification. This research has enabled the development of a soiling index (the TSI by Thornbush, 2014a) based on surface areal measurements of lightness. Thornbush and Viles (2004) originally introduced the Integrated Digital Photography and Image Processing (IDIP) method, which was subsequently calibrated by Thornbush (2008) for outdoor application as the O-IDIP.…”