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Extraction and Reconstruction of Zebra Crossings from High Resolution Aerial Images

机译:高分辨率航空影像中斑马线的提取与重建

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In this paper, an automatic approach for zebra crossing extraction and reconstruction from high-resolution aerial images is proposed. In the extraction procedure, zebra crossings are extracted by the JointBoost classifier based on GLCM (Gray Level Co-occurrence Matrix) features and 2D Gabor Features. In the reconstruction procedure, a geometric parameter model based on spatial repeatability relationships is globally fitted to reconstruct the geometric shape of zebra crossings. Additionally, a group of representative experiments is conducted to test the proposed method under interfered conditions, such as zebra crossings covered by pedestrians, shadows and color fading. Furthermore, the performance of the proposed extraction method is compared with the template matching method. Finally, the results show the validation of our proposed method, both in the extraction and reconstruction of zebra crossings.
机译:本文提出了一种从高分辨率航空影像中提取和重构斑马线的自动方法。在提取过程中,JointBoost分类器基于GLCM(灰度共生矩阵)特征和2D Gabor特征提取斑马线。在重建过程中,基于空间重复性关系的几何参数模型被全局拟合以重建斑马线的几何形状。此外,还进行了一组代表性实验,以在受干扰的条件下(例如,行人覆盖的斑马线,阴影和褪色)测试该方法。此外,将所提出的提取方法的性能与模板匹配方法进行了比较。最后,结果表明了我们提出的方法在斑马线的提取和重建中的有效性。

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