Since deformation estimation may lead to errors occurring when the camera vibrates, it is necessary to remove the image global motion before computing real bridge deformation. In this study, a combination of image motion correction algorithm and 2D image-based deformation measurement technique was utilized to address the issue of camera motion during the image data acquisition for bridge deformation measurement. Based on the proposed methodology, the image motion parameters were estimated by defining an effective sub-image in the image and using Iterative Affine Motion Estimator. Then the estimated parameters were applied to all pixels of each captured image to remove the motion effect. Finally, the corrected images were used to analyze by a 2D image-based deformation measurement technique in order to extract and measure real bridge deformation by tracking artificial or natural targets. The proposed methodology was validated by two experiments in the lab and field environments. Achieved results show the accuracy and reliability of the proposed methodology.

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Noise pollution is considered as one of the effective factors affecting people's quality of life in urban areas throughout the world. Traffic is a major source of noise in urban areas with wide ranging effects on human. The present study aims to determine the mean of noise levels in old and new urban fabric and their relationship with the traffic flow. Acoustic survey was performed during one week in each month of the summer in assigned stations. In this investigation, using a sound level meter and BS 7445-1-2003, BS 7445-3-1991, Leq 10 min was measured and the percentage of highly annoyed people was estimated. The data were analyzed by using statistical tests and SPSS software. The results show that the mean of noise levels measured in all stations during the three months of the summer was higher than the standard limit. The relationship between the mean of noise level and the traffic flow in areas in new fabric was significant but not in those in old fabric. Higher rates of noise pollution in old fabrics and lack of significant relationship with the traffic flow in those points show that noise pollution can be reduced in the city to a great extent by considering effective traffic rules, widening crowded streets, and improving those conditions that govern urbanization. Of course, the amount of the porosity of asphalt, bumpy streets, and even technical defect of motor vehicles should not be ignored.