基于区域加权霍夫变换的建筑立面图像鲁棒线检测

T. Tsenoglou, N. Vassilas, D. Ghazanfarpour
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引用次数: 1

摘要

本文提出了一种鲁棒的基于区域的加权霍夫变换方法,用于检测建筑立面质量差图像中的直线。经过一个典型的预处理阶段,包括颜色到灰度的变换,使用Otsu的自动阈值选择方法进行二值化,形态学打开和分解成连通区域,然后在每个区域上拟合一个最小的边界矩形。然后使用矩形度度量,以便从进一步处理中过滤出矩形度分数低的区域。最后,使用适当设计的核计算每个区域对累加器阵列的贡献,该核模拟与区域最小边界矩形的几何中心和方向相关的不确定性。在视觉条件受损或低精度传感器(例如热图像)拍摄的立面图像上,将所提出的方法与其他霍夫变换算法进行比较,表明我们的方法在检测线条和/或线性结构方面的准确性有所提高。该方法还成功地用于通过消失点估计进行图像校正。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust Line Detection in Images of Building Facades using Region-based Weighted Hough Transform
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.
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