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A robust region-based weighted Hough Transform method for the detection of straight lines in poor quality images of building facades is presented in this work. Following a typical preprocessing stage that includes color to grayscale transformation, binarization using Otsu's automatic threshold selection method, morphological opening and decomposition into connected regions a minimum bounding rectangle is then fitted to each region. A measure of rectangularity is then used in order to filter out regions with low rectangularity scores from further processing. Finally, the contribution of each region to the accumulator array is computed using an appropriately designed kernel that models the uncertainties associated with the geometrical center and orientation of the region's minimum bounding rectangle. Comparisons performed on facade images taken with impaired visual conditions or with low accuracy sensors (e.g. thermal images) between the proposed method and other Hough Transform algorithms, show an improved accuracy of our method in detecting lines and/or linear formations. The proposed method is also used with success for image rectification through vanishing points estimation.