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Background: Color accuracy plays a major role in creating an esthetic prosthesis. Photos taken with DSLR cameras have been the most frequent means of recording and transferring the color of teeth. Mobile phone cameras are emerging as a popular alternative to DSLR cameras due to its convenience. Our aim was to compare the color difference (ΔE) between the pictures taken with DSLR cameras and mobile cameras with and with­out using flash. Methods: Photos of right maxillary central incisors of patients (n=60) were taken with DSLR camera and mobile camera with and without using flash. The pictures were standardized with gray card and processed in Adobe Photoshop Lightroom CC software and the L*a*b* values of the pictures were compared to find the difference in color. Results: The percentage of agreement (ΔE≤2.7) for the difference of color between DSLR camera and mobile phone cameras without using flash (ΔE1) was 3.3% and with using flash (ΔE2) was 1.7%. The coefficient of agreement (using Kappa coefficient) between (ΔE1) and (ΔE2) showed total disagreement (kappa value =-.02). The mean values of ΔE1 was (8.3±3.3) and ΔE2 was (7.23±2.4). Conclusions: It was concluded that the color of mobile camera with or without using flash could not be considered as an acceptable method of recording color of teeth.

Modeling a structure in the virtual world using three-dimensional (3D) information enhances our understanding, while also aiding in the visualization, of how a structure reacts to any disturbance. Generally, 3D point clouds are used for determining structural behavioral changes. Light detection and ranging (LiDAR) is one of the crucial ways by which a 3D point cloud dataset can be generated. Additionally, 3D cameras are commonly used to develop a point cloud containing many points on the external surface of an object around it. The main objective of this study was to compare the performance of optical sensors, namely a depth camera (DC) and terrestrial laser scanner (TLS) in estimating structural deflection. We also utilized bilateral filtering techniques, which are commonly used in image processing, on the point cloud data for enhancing their accuracy and increasing the application prospects of these sensors in structure health monitoring. The results from these sensors were validated by comparing them with the outputs from a linear variable differential transformer sensor, which was mounted on the beam during an indoor experiment. The results showed that the datasets obtained from both the sensors were acceptable for nominal deflections of 3 mm and above because the error range was less than ±10%. However, the result obtained from the TLS were better than those obtained from the DC.

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