# Image Quality Assessment of Digital Image Capturing Devices for Melanoma Detection
## 2 Materials and Methods
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Camera Model** & **Width \(\times\) Length (px)** & **Camera Lens** \\ \hline iPhone 5s & \(3264\times 2448\) & 4.15 (in 35 mm: 29 mm) f/2.2 \\ iPhone 7 & \(4032\times 3024\) & 3.99 (in 35 mm: 29 mm) f/1.8 \\ iPhone XR & \(4032\times 3024\) & 4.25 (in 35 mm: 29 mm) f/1.8 \\ Samsung S10 (SM-G975F) & \(4032\times 3024\) & 6.00 (in 35 mm: 26 mm) f/2.4 \\ HUAWEI P10 (EVA-L09) & \(3968\times 2976\) & Leica 4.05 (in 35 mm: 27 mm) f/2.2 \\ Canon EOS M10 & \(5184\times 3456\) & 30 (EF-M 15-45) f/3.5–6.3 \\ Canon EOS 800D (FotoFinder) & \(6000\times 4000\) & Tokina AT-X M35 PRO DX 2.8 \\ Medicam 1000s (FotoFinder) & \(1920\times 1080\) & - \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Cameras applied in the test. Figure 1: The used edge spatial frequency response (eSFR) ISO test chart target. Sixteen colours are similar to the industry-standard 24-colour test. Slanted-edge squares where the eSFR was calculated on 57 regions of interest (ROI) in the MATLAB Image Processing Toolbox (MathWorks, Natick, MA, USA); the results, calculated from the ROI Nr. 5, represent the sharpness at the image edges, and, from the ROI Nr. 29 the sharpness in the image centres. During the exposure, a camera was fixed on a tripod to avoid vibration, thereby reducing the production of blurry image results [17]. A black fabric material was used to cover the walls in the testing room, to prevent the influence of ambient or other light sources. Calibrated LED lights were applied to illuminate the chart with colour correlated temperatures (CCT) of 3200 K and 5500 K (positioned on either camera side at 45 degree angles, and 2 m in front of the chart table), to estimate the response of the camera to the typical light conditions, as used in the home or hospital environments [8; 9]. The intensity of 750 lux and the evenness of light uniformity across the target area were controlled on the different chart positions by the use of a Gossen Digisky light meter. Our approach was to measure the colour response of a captured image from a reference colour. For this purpose, the test chart was illuminated with lights of colour temperatures 3200 K and 5500 K. Secondly, the reference colours of the Xrite reference chart [43] were measured as captured through a handheld dermoscopy device and illuminated by the integrated polarised LED light. The colours from the captured images were, after that, evaluated, and compared to the reference value by the CIELAB colour difference \(\Delta E\), which is proportional to the colour difference as seen by a human observer [30; 41]. Dermoscopy images were captured through the DermLite 4 DL handheld dermoscopy device, (Dermlite, 3 Gen, Inc., San Juan Capistrano, CA, USA) [44], which was connected by a magnetic ring adapter to a mobile phone and a mirrorless digital camera. The white point of the handheld Dermlite DL4 dermoscope was measured from the lighting profile on a UPRek MK350 spectrometer. For medical applications, a reference chart with a range of human skin colours is also necessary [30]. Reference skin tone colours in dermoscopy images were captured one-by-one from the Xrite ColorChecker chart, as is shown in Figure 3a. Consequently, colour detection is of great diagnostic importance, and a proper evaluation of colours and their relative distribution is essential for achieving the correct clinical diagnosis of a pigmented skin lesion [27]. During melanoma diagnosis, the dermatologist identifies six different colours: black, dark brown, light brown, blue, grey, red and white [27; 28; 45]. The selection of six reference skin colours of the Digital ColorChecker was based on two facts. First, the melanin and its brown colour determine the basic skin tan, and, at the same time, it represents the essential colour in a dermoscopy image of a skin mole [27]. Identifying multiple shades of brown allows conclusions about the quantity, position and distribution of melanin, which is the primary tool for recognition of melanoma in the earliest stage of the disease.